in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can efficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with per University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database haduk framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve effic iciency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavy heav in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now the data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for country learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as Apachi Hado to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structure semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the data to the responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on databased knowledge now data Engineers are well vered in working with relational databases like MySQL Oracle postu SQL and even non- relational databases like mongodb Cassandra and Rus they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop apachi spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a n engineer in Us is around $1 17,345 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in area such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is wiely regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numi and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and Rober squaring capabilities nosql databases like mongodb Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now e plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from divers sources into a central repository well moving ahead you need to master big data to tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apache spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and Apache Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hadoop distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally apachi Kafka which is an open source distributed streaming platform deved by the Apache softare Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data SCI and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that demands a combination of technical skills domain knowledge and practic experience to climb the tricky Terran of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upscaling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with puu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the post graduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascin and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are VAR variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality in integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as Apachi Hado to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consol validate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others UR efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set bring software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well verged in working with relational databases like MySQL Oracle postu SQL and even non- relational databases like mongodb Cassandra and RIS they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data engineers pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data beare houses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop Apachi spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $1 17,345 per year and it can go as high as $157,000 per year year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is Val regarded as one of the most suitable languages for dat engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numpy and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and Rober squaring capabilities no SQL datab databases like mongod DV Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now e plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process LGE data sets in a cloud environment therefore having experience with tools such as Apache spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally Apache Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fault orend streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo Kio powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst but by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to clim the tricky Terren of the data engineering landscape and with that we' have come to the end of today's video guys I hope you understood this data Engineer Road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upscaling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data poses a significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play Vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive Road mapap with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with Peru University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing apachi Kafka for data pipelines and working with big data on AWS and Ure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and asking anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to kick start your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with hands salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as apachi Hado to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data Pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well version working with relational databases like MySQL Oracle post SQL and even non- relational databases like mongodb Cassandra and RIS they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like tap powerbi and Q view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop Apachi spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $7,350 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer in 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is wiely regarded as one of the most suitable languages for data engineering its user-friendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas NPI and CPI in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well defined schema transactional support and Robber squaring capabilities nosql databases like mongodb Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now eer plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apache spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for bat processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map redu programming model for distribution Pro processing and finally Apachi Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fault or in streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo Q powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to clim the tricky Terren of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upskilling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with puu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organization can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now company across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipel development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as apachi Hadoop to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance data datas design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reli ability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle post SQL and even non- relational databases like mongodb Cassandra and redus they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like apachi Hadoop Apache spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in add addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $7,350 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay premium for skill data engineering professionals who can help help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly DW into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a program language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is Wily regarded as one of the most suitable languages for data engineering its user-friendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numi and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle my Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well- defined schema transactional support and Rober squaring capabilities no SQL databases like mongod DB Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data engineer specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now e plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apache spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hadoop distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally apachi Kafka which is an open source distri uted streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fall orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of service serves and Solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires careful navigation right from the beginning it's a journey that demands a combination ofch technical skills domain knowledge and practical experience to climb the tricky Terren of the data engineering landscape and with that we' have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upskilling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with puu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and askme anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's datadriven landscape now the main question is why pursue a career in data engineering ing well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers second diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you g experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as Apachi Hado to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like my SQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle postu SQL and even non-relational databases like mongodb Cassandra and redis they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like TBL powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop Apachi spark for Distributing Computing real-time data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying data solution so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $1 17,345 per year and it can go as high as as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lak per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital eror now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer in 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is well regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numi and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well- defined schema transactional support and squaring capabilities no SQL databases like mongodb Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now e plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apachi spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distributed Pro processing and finally Apachi Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fall orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to clim the tricky Terren of the data engineering landscape and with that we've come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upscaling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to ner up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skill data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with puu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing apachi Kafka for data pipelines and working work with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expert you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as a Apachi Hadoop to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimiz Iz ation now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set brending software engineering data management big data and cloud computing expertise firstly having a good knowledge on database based knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle postu SQL and even non- relational databases like mongodb Cassandra and redis they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statist SS and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills and data visualization tools like TBL powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing frame Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop Apachi spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $1 17,345 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies you order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in area such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is wiely regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numi and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have it in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and Robber squaring capabilities nosql databases like mongodb Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now ET plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apachi spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hardo distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally Apachi Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionize The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive Road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires careful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to climb the tricky ter of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upscaling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engine postgraduate program offered by simply learn in collaboration with pu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM maons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the post graduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what ises a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as apachi Hadoop to handle large volumes of data parel processing and distributed computing data warehousing and integration now data engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system help to identify and resolve issues promptly they perform routine maintenance back backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle post SQL and even non- relational databases like mongodb Cassandra and redis they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like TBL powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like apachi Hadoop apachi spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $1 17,345 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in area such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering of programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is wiely regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas nump and scipi in order to efficiently handle and transform data in addition you can also Master language just like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rtpms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and Robber squaring capabilities nosql databases like mongod DB Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now ET plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as apachi spark which is a powerful distributed processing freame framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally Apachi Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fault orend streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud Computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data engineer support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't need conf CH here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires careful navigation right from the beginning beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to climb the tricky Terren of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upscaling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs and Cutting Edge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to Pur your career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with P University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to kick start your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high Dem demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a compe compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological Advan an MS acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as Apachi Hado to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system help to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the dat data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle post SQL and even non-relational databases like mongodb Cassandra and brius they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like tap powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with lar scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop Apache spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $7,350 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer does doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is wiely regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numi and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the r space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle my Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well Define schema transactional support and Robber squaring capabilities nosql databases like mongod DV Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now ET plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apachi spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally apachi Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo QQ powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that demands a combination of technical skills domain knowledge and practical experience to claim the tricky Terren of the data engineering landscape and with that we've come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts cover in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upscaling whether you're a student aiming to learn today's top skills or a working professional looking to advance your your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transform data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with puu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as Apachi Hadoop to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi- disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle post SQL and even non-relational databases like mongodb Cassandra and brius they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and QC view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop Apache spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of data engineer in Us is around $7,350 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dwell into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer in 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is Val regarded as one of the most suitable languages for data engineering its user-friendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numi and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and robust squaring capabilities nosql databases like mongodb Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now e plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as dat Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apachi spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally Apachi Kafka which is an open source distributed streaming platform deved by the Apachi software Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data engineer support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effective l so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to climb the tricky Terren of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upskilling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue your career as a data engineer or want to transition into the the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with puu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large operations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a dat daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as apachi Hado to handle large volumes of data parallel processing and distributed computing data warehouse and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle postu SQL and even non- relational databases like mongodb Cassandra and redis they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like apachi Hadoop apachi spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $7,350 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital error now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer in 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is Val regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numai and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and robust squaring capabilities no SQL databases like mongodb Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now eer plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apache spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distrib Pro processing and finally Apachi Kafka which is an open source distributed streaming platform deved by the Apache software Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn m and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to climb the tricky Terren of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upskilling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture deit AT&T are hiring experts who can help them leverage dat efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with puu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hado framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analy Tex and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a d engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as Apachi Hado to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engine ER now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well verion working with relational databases like MySQL Oracle post SQL and even non- relational databases like mongodb Cassandra and redis they should have a strong understanding of database design schema modeling indexing and per optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good knowledge and skills on data visualization tools like T powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop Apachi spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $1 17,345 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital a now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in area such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 20123 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is vly regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numai and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have it in depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rtpms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and Rober squaring capabilities no SQL databases like mongodb Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data engineer specialize in designing and building data infrastructures including data pipelines and data warehouses the responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now e plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as apachi spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for bat processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally apachi Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle real time high throughput and fall orent streaming data and finally learning cloud computing well cloud computing has revolutionize The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires careful navigation right from the beginning it's a journey that demands a combination of technical skills domain knowledge and practical experience to clim the tricky teror of the data engineering landscape and with that we' have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upscaling whether you're a student aiming to learn today's top skills or a work professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to career your success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to ner up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with pu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop phas workk spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and askme anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further do let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into Compu compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what is a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as Apachi Hadoop to handle large volumes of data parel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization index T in and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system help to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle post SQL and even non- relational databases like mongodb Cassandra and redis they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them up apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like TBL powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hado Apachi spark for Distributing Computing real-time data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $1 17,345 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies you know to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is Wily regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numai and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and Robber squaring capabilities no SQL databases like mongod DB Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the the process of extracting data from various sources transforming it into a consistent and structured format now ET plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apachi spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally Apachi Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionized the way business to store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo Q powerbi as well as machine learning tools and algorithms can also gain your more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data engineer support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires careful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to climb the tricky Terren of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data Engineer Road mapap and if you have any further queries regarding ing any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upscaling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs and cutting Edge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to ner up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to your career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with puu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally prob solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as apachi Hadoop to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database qu and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like my SQL Oracle post dsql and even non-relational databases like mongodb Cassandra and Rus they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data beare houses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like TBL powerbi and QC view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like a AI Hadoop Apache spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $1 17,345 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dwell into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong found on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is wiely regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numi and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the risk space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle my Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and Rober squaring capabilities nosql databases like mongodb Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now e plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apachi spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally Apachi Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo Q powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data engineer support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires careful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to climb the tricky Terren of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thanks than you and keep learning staying ahead in your career requires continuous learning and upskilling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with puu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course length is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can get a Cooperative Edge improve improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are in investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various industri such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as Apachi Hado to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi- disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle postu SQL and even non- relational databases like mongodb Cassandra and RIS they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate process processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data beare houses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop apachi spark for Distributing Computing real-time data streaming and data processing can be quite helpful and in addition data Engineers also often work work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of ofer data engineer in Us is around $1 17,345 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a programming language is Paramount now pyth python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is Val regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numpy and CPI in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and Robber squaring capabilities nosql databases like mongod DV Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipeline and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now e plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master big data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apache spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally apachi Kafka which is an open source distributed streaming platform deved by the apach P software Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions if in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires careful navigation right from the beginning it's a journey that demands a combination of technical skills domain knowledge and and practical experience to climb the tricky Terran of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upscaling whether you're a student aiming to learn to today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and M maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with Peru University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language language SQL database haduk framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as Apachi hadu to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well vered in working with relational databases like MySQL Oracle postu SQL and even non-relational databases like mongodb Cassandra and redis they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data beare houses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and qck view can help you gain a competitive advantage AG in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop Apachi spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around 11 17,345 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in area such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is vely regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numai and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well- defined schema transactional support and robust squaring capabilities no databases like mongod DB Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now e plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apache spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for bat processing realtime streaming machine learning and graph processing and apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally Apachi Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithm THS can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to claim the tricky Terren of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upscaling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive cab calog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to ner up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data posesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive roadmap with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with Peru University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape AP in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Heth Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems requ for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as apachi Hado to handle large volume of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipeline databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data engineers are well version working with relational databases like MySQL Oracle postu SQL and even non- relational databases like mongodb Cassandra and Rus they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help with you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehous next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop Apachi spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should process in order to thrive in today's technological domain now let us talk about the Sal and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $1 17,345 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 20123 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is Wily regarded as one of the most suitable languages for data engineering its user-friendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as FAS numai and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and Robber squaring capabilities nosql databases like mongod DV Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data engineer specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now ET plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apache spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for bat processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally Apachi kka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fault or and streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like table Q powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to clim the tricky Terren of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts cover in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you as ass at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upskilling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resour F organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM accent Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with pu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything session to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as dat data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as apachi Hadoop to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Manu systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure his system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle post SQL and even non-relational databases like mongodb Cassandra and Rus they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java scale to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with lar scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like apachi Hadoop apachi spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $1 17,345 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay premium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in area such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is wiely regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numi and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbm such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and Robber squaring capabilities no SQL databases like mongod DB Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now ET plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central Repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as apachi spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally apachi Kafka which is an open distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range R of services and solutions in addition having a good knowledge on data visualization tools like TBL Q powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data engineer support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that demands a combination of technical skills domain knowledge and practical experience to climb the tricky Terren of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upskilling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to no more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem system they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with Peru University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and askme anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as Apachi Hado to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database a API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multidisiplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle postu SQL and even non-relational databases like mongodb Cassandra and Rus they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and CC view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop Apachi spark for Distributing Computing real-time data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying dat Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $7,350 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a premium for skill data engineering professionals who can help them harness the power of their data in today's digital error now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dwell into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is wiely regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numi and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database system is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server myql are widely adopted for managing structured data they provide a well-defined schema transactional support and Robber squaring capabilities no SQL databases like mongod DV Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now e plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apachi spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map redu programming model for distribution Pro processing and finally Apachi Kafka which is an open source distributed streaming platform deved by the Apache software Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and require skillful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to climb the tricky Terren of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upskilling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with Peru University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing apachi Kafka for data Pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand and what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data Driven Landscape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recognize the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various industry such as technology Finance Healthcare e-commerce and much more Additionally you can choose to work up in large corporations startups consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly evolves new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what does a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as as Apachi Hado to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle postu SQL and even non- relational databases like mongodb Cassandra and Rus they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with languages such as python Java Scala to develop data pipelines automate processes and perform data manipulation tasks data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like Apachi Hadoop Apachi spark for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $7,350 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay premium for skill data engineering professionals who can help them harness the power of their data in today's digital error now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in area such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is wiely regarded as one of the most suitable languages for data engineering its userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numpy and scipi in order to efficiently handle and transform data in addition you can also Master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preferences and expertise now rdbms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well-defined schema transactional support and Rober squaring capabilities no SQL databases like mongodb Cassandra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now eer plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse sources into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apache spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally Apachi Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle realtime high throughput and fault orent streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithms can also gain you more Advantage as a data engineer now understanding machine learning and deep learning algor thems aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 2023 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to claim the tricky Teran of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts cover in today's tutorial let us know in the comment section below and a team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upscaling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to nerd up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making next nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the raw data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're looking to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with puu University and IBM provides an excellent opportunity for professionals to gain valuable exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hardo framework spark for data processing apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and ask me anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the postgraduate program to Kickstart your journey in data engineering the course link is added in the description box below make sure to check that out so without any further Ado let's get started with today's topic firstly let us understand what is data engineering data engineering involves building pipelines that extract transform and analyze large scale data to provide valuable insights about a business operation Now by leveraging these insights organizations can gate a Cooperative Edge improve efficiency and drive innovation in today's data driven landcape now the main question is why pursue a career in data engineering well data engineering can be a fascinating and fulfilling career the reasons for learning data Engineering in nowadays is because of its high demand and growing uh landscape in our current business technological trends like the demand for data Engineers is constantly increasing as organizations recogniz the value of data driven decision making now companies across various Industries are investing heavily in data infrastructure analytics and machine learning creating a high demand for skilled data Engineers secondly diverse Industries now there are V variety of job opportunities in the field of data engineering data engineering offers a wide range of job opportunities where you can work in various Industries such as technology Finance Healthcare eCommerce and much more Additionally you can choose to work up in large corporations startups Consulting firms or even as a freelance data engineer next competitive salary now data engineer skills are highly valued in the job market nowadays and a competitive compensation is what makes a part for a data engineer in the market this demand often translate into competitive compensation packages and opportunities for career growth as you gain experience and expertise you can attain leadership roles with handsome salaries and finally problem solving and continuous learning now data engineering is a field that constantly EVS new technologies tools and Frameworks emerge regularly offering opportunities for continuous learning and growth as a data engineer you can stay at the Forefront of technological advancements acquire new skills and expand your knowledge to adapt to changing industry Trends now let us understand what do a data engineer do now a data engineer is responsible for Designing constructing and maintaining the infrastructure and systems required for the efficient and reliable handling of large volumes of data so on a daily basis a data engineer involves in many activities such as data pipeline development now data engineers build robust and scalable data pipelines that extract transform and load data from various sources into storage and processing systems ensuring data quality integrity and efficient data movement providing Big Data Solutions now data Engineers work with big data technology such as apachi Hado to handle large volumes of data parallel processing and distributed computing data warehousing and integration now data Engineers design and Implement data warehouses which are centralized repositories that store structured semi-structured and unstructured data data Engineers integrate data from multiple sources including database API and external systems in order to consolidate and reconcile data from various sources ensuring data consistency and coherence performance and optimization now data Engineers optimize data processing workflows database queries and system performance to minimize latency improve efficiency and enhance overall system performance database design and management now database Engineers design create and maintain databases selecting appropriate database Management Systems like MySQL Oracle and others ensuring efficient data organization indexing and query performance and finally monitoring and maintenance now data Engineers monitor data pipelines databases and system Health to identify and resolve issues promptly they perform routine maintenance backups and upgrades to ensure system reliability and stability so these are some of the day-to-day responsibilities of a data engineer now let us now move ahead and discuss some of the data engineer skill set now becoming a data engineer requires a multi-disciplinary skill set branding software engineering data management big data and cloud computing expertise firstly having a good knowledge on database knowledge now data Engineers are well versed in working with relational databases like MySQL Oracle postu SQL and even non- relational databases like DB Cassandra and redis they should have a strong understanding of database design schema modeling indexing and query optimization statistics now just like uh the field of data science and data analytics having a good knowledge on statistics for data Engineers can set them apart from the rest so having a good analytical skills on mathematical models and statistics and probability can help you stand out in the market programming tools now Proficiency in programming language is crucial for data Engineers they commonly work with Lang ages such as python Java Scala to develop data pipelines automate processes and perform data manipulation task data integration and ETL pipeline now understanding the concepts and techniques related to data warehousing is important for data Engineers ETL pipeline which is a part of data warehousing is responsible for extracting data from various sources transforming it into a usable format and loading into Data warehouses next machine learning now although data Engineers doesn't have much Reliance on machine learning but having a good knowledge on machine learning can also provide you an edge over the others having a good Knowledge and Skills on data visualization tools like T powerbi and qck view can help you gain a competitive advantage in the job market as well and finally big data and cloud computing now data Engineers work with large scale data processing Frameworks and Technologies and having a good knowledge on Big Data tools like apachi Hadoop apachi sparkk for Distributing Computing realtime data streaming and data processing can be quite helpful and in addition data Engineers also often work on cloud platforms like Amazon web services Microsoft Azure gcp for building and deploying Data Solutions so all these are some of the main skill set that a data engineer should possess in order to thrive in today's technological domain now let us talk about the salary and job prospects of a data engineer now data Engineers are currently high in demand which often translate to attractive salary p packages and career growth prospects now according to glass door the average salary of a data engineer in Us is around $1 17,345 per year and it can go as high as $157,000 per year similarly in India if you talk about the average salary it is around 9.5 lakh per year and can go high as high as 17 lakhs per year so as companies invest heavily in data driven initiatives they're willing to pay a pre prium for skill data engineering professionals who can help them harness the power of their data in today's digital era now becoming a data engineer doesn't happen overnight you need to have a blend of technical skills practical experience on various tools and Technologies in order to become a data engineer so let us now directly dve into the road map on how to become a data engineer firstly have a strong foundational knowledge now develop a strong foundation in mathematics Ma matics and statistics just like data science and data analytics do now data engineering heavily relies on mathematical statistical Concepts such as probability and various statistical tools so begin by strengthening your knowledge in areas such as linear algebra calculus probability Theory and statistical analysis now moving ahead you need to have a strong foundation on any of a programming languages now to embark on a journey as a data engineer 2023 mastering a programming language is Paramount now python stands out as an ideal choice to begin your programming journey in this field providing a solid foundation and structured thinking python is Wily regarded as one of the most suitable languages for data engineering it's userfriendly syntax and readability makes it easy to learn and understand it offers an extensive range of libraries and Frameworks such as pandas numpy and scipi in order to efficiently handle and transform data in addition you can also master languages like R and Scala which are more popular these days for data Engineers moving ahead have a in-depth knowledge on databases now as a data engineer working with database systems is a fundamental aspect of your role as you play a vital role in handling large data sets efficiently now with the plethora of dbms options available it's important to note that you don't need to be expert in all of them the choice of dbms often depends on the space requirements and preferences of the company you work for as well as your own preference and expertise now rtpms such as Oracle Microsoft SQL Server MySQL are widely adopted for managing structured data they provide a well- defined schema transactional support and Rober squaring capabilities no SQL databases like mongodb cassendra are designed to handle unstructured or semi-structured data they offer flexibility in data modeling horizontal scalability and high performance for specific use cases well moving ahead data warehousing and ETL Pipelines now data Engineers specialize in designing and building data infrastructures including data pipelines and data warehouses they're responsible for efficiently collecting transforming and storing data from various sources now ETL stands for extract transform and load and it refers to the process of extracting data from various sources transforming it into a consistent and structured format now e plays a crucial role in data warehousing by enabling organizations to integrate and consolidate data from diverse procces into a central repository well moving ahead you need to master Big Data tools now handling large data sets is a common requirement for data engineers and to accomplish this effectively you often need to work with big data tools now these tools complement their knowledge of cloud computing as data Engineers frequently Implement code that can handle and process large data sets in a cloud environment therefore having experience with tools such as Apache spark which is a powerful distributed processing framework that enables fast and scalable data processing it provides a unified and flexible platform for batch processing realtime streaming machine learning and graph processing and Apachi Hadoop which is an open source framework for distributed storage and processing of large data sets across cluster of computers it includes the Hado distributed file system or in short known as hdfs for scalable storage and map reduce programming model for distribution Pro processing and finally Apache Kafka which is an open source distributed streaming platform developed by the Apache software Foundation it is used to handle real-time high throughput and fault orend streaming data and finally learning cloud computing well cloud computing has revolutionized The Way businesses store process and manage their data leading to a growing demand for engineers skilled in cloud computing tools and platforms now the three major Cloud servicing providers which is Microsoft Azure AWS and gcp dominate the cloud computing market and offer a wide range of services and solutions in addition having a good knowledge on data visualization tools like tblo qio powerbi as well as machine learning tools and algorithms can also gain your more Advantage as a data engineer now understanding machine learning and deep learning algorithms aren't a must for data engineer however as data Engineers support the data scientist teams it will provide to be helpful if they learn ML and DL thoroughly now don't get confused here with the role of a data scientist and a data engineer while data engineering data science and data analysis are related fields they do have distinct roles and responsibilities now the role of a data engineer is to bridge the gap between data scientist and data analyst by providing them with the necessary data and tools to perform their task effectively so that was a comprehensive road map on how to become a data engineer in 20123 becoming a data engineer has its own share of challenges and requires skillful navigation right from the beginning it's a journey that Demands a combination of technical skills domain knowledge and practical experience to clim the tricky Terren of the data engineering landscape and with that we have come to the end of today's video guys I hope you understood this data engineer road map and if you have any further queries regarding any of the concepts covered in today's tutorial let us know in the comment section below and our team of experts will be more than happy to let you assist at the earliest until next time thank you and keep learning staying ahead in your career requires continuous learning and upskilling whether you're a student aiming to learn today's top skills or a working professional looking to advance your career we've got you covered explore our impressive catalog of certification programs in cuttingedge domains including data science cloud computing cyber security AI machine learning or digital marketing designed in collaboration with leading universities and top corporations and delivered by industry experts choose any of our programs and set yourself on the path to Career Success click the link in the description to know more hi there if you like this video subscribe to the simply learn YouTube channel and click here to watch similar videos to ner up and get certified click here in the era of digital transformation data has become vital to the functioning of businesses in all sectors this data possesses significant potential for fostering business expansion attaining a Competitive Edge and facilitating informed decision making nevertheless to harness the power of this data resourcefully organizations needs experts who can proficiently handle and manipulate it this is where data Engineers come into picture and play a vital role in the overall data ecosystem they are responsible for building and maintaining the infrastructure and systems that enable efficient data processing storage and accessibility data engineering is arguably one of the fastest growing positions in technological sector thanks to the rise of big data and data science applications and that is why companies like Google Amazon IBM Accenture Deo AT&T are hiring experts who can help them leverage data efficiently interact with the rod data clean it polish it and making it analysis ready on that note hello everyone welcome to Simply learn in today's video we'll guide you through the essential steps to embark on a journey towards becoming a skilled data engineer with a comprehensive road map with that having said if you're Le to pursue a career as a data engineer or want to transition into the field of data engineering then our data engineering postgraduate program offered by simply learn in collaboration with pu University and IBM provides an excellent opportunity for professionals to gain valuable EXP exposure in the field the data engineering course covers a range of important topics including Python language SQL database Hadoop framework spark for data processing Apachi Kafka for data pipelines and working with big data on AWS and Azure Cloud infrastructures the program utilizes various learning methods such as live sessions industry projects IBM hackathons and askme anything sessions to provide a comprehensive and practical learning experience so what are you waiting for enroll now in the post
