How to become a Data Engineer

Becoming a Data Engineer is an in-demand career path. It requires deep expertise in Data Engineering and a strong network to carry you along. Here are some resources to help you on your journey.

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Why should you become a 
Data Engineer?

Data Engineer

Demand for experts in Data Engineering is growing rapidly. Companies are looking for people with deep expertise in the field of Data Engineering to help them build their products and services.

As a result, Data Engineers are in high demand and command high salaries. According to leading sources, the median salary for a Data Engineer is $110,000 and a senior Data Engineer can earn up to $140,000. Even entry-level positions can command great salaries.

No wonder that interest in a career in Data Engineering is growing rapidly. Explore the resources below to learn more about how to become a Data Engineer.

Best books to build Data Engineering understanding.

A well-written and thorough book can be an amazing path to build deeper understanding and also act as a handbook as you discover the internet's vast resources.

These are our and our experts top picks to get started building career-relevant skills.

Data Engineering Cookbook

Data Engineering Cookbook

Five types of content are in this book: Articles the author wrote, links to his podcast episodes (video & audio), more than 200 links to helpful websites he like, data engineering interview questions and case studies.

Database and Expert Systems Applications

Database and Expert Systems Applications

The Database and Expert Systems Application -DEXA - conferences are mainly oriented to establish a state-of-the art forum on Database and Expert System applications. But Practice without Theory has no sense, as Leonardo said five centuries ago. In this Conference we try a comprornise between these two complementary aspects. A total of 5 sessions are application-oriented, ranging from classical applications to more unusual ones in Software Engineering.

The Data Warehouse Toolkit

The Data Warehouse Toolkit

One of the most dramatic new developments in database design, the dimensional data warehouse is a powerful database model that.significantly enhances managers' ability to quickly analyze large, multidimensional data sets. Written by the leading proponent of this revolutionary new approach, this valuable book/CD toolkit outfits you with all the nuts-and-bolts information you need to design, build, manage, and use dimensional data warehouses for virtually any type of business application, as well as software for querying dimensional data warehouses.

Big Data

Big Data

Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built.


Designing Data-Intensive Applications

Designing Data-Intensive Applications

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?

Data Pipelines Pocket Reference

Data Pipelines Pocket Reference

Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack.

Advanced Topics in Database Research

Advanced Topics in Database Research

Advanced Topics in Database Research is a series of books on the fields of database, software engineering, and systems analysis and design. They feature the latest research ideas and topics on how to enhance current database systems, improve information storage, refine existing database models, and develop advanced applications.

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Courses to deepen your Data Engineering skills.

These days, courses are no longer a sequence of videos. They are usually accompanied by projects and a learning community, keeping you accountable and on the path.

Our experts recommend these courses, from free selections to paid programs.

Data Engineering Foundations

Data Engineering Foundations

Build the Foundation for a Data Engineering Career. Develop hands-on experience with Python, SQL, and Relational Databases and master the fundamentals of the Data Engineering ecosystem.

Data Engineering

Data Engineering

Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets. At the end of the program, youโ€™ll combine your new skills by completing a capstone project.

Introduction to Data Engineering

Introduction to Data Engineering

Learn about the world of data engineering with an overview of all its relevant topics and tools!

Data Engineering Career Path

Data Engineering Career Path

Data engineering has seen explosive growth recently as more industries depend on data to drive key business decisions. Take advantage of the surge in demand by becoming a data engineer with Dataquest.

Advanced Database Administration

Advanced Database Administration

Learn the fundamentals of administering relational database management systems, including managing concurrency and creating objects in the database

Data Engineering on Google Cloud platform

Data Engineering on Google Cloud platform

End to end batch processing,data orchestration and real time streaming analytics on GCP

Data engineering and smart analytics

Data engineering and smart analytics

The need for data analysis skills grew by 86% from 2013 to 2018. 1 Become data-driven with Google Cloud. Leverage data and gain real-time insights that improve your decision-making and accelerate innovation. Learn how to design and build data processing systems.

Get the guidance you need to become a Data Engineer

There is no better source of accountability and motivation than having a personal mentor. What used to be impossible to find is now just two clicks away! All mentors are vetted & hands-on!

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Supercharge your transition into data engineering with Gaurav, a passionate Senior Data Engineer at Amazon. With 9 years of experience, Gaurav excels in designing data platforms, implementing architectures like Data lake, Lakehouse, and Data mesh. Expertise in building cloud-based platforms, data pipelines, and ensuring governance and security. Benefit from Gaurav's โ€ฆ

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Hi there! As a seasoned Data & Analytics specialist, I have over 10 years of experience with leading data teams and implementing data & analytics solutions for a range of private and public companies In addition to my professional experience, I am also a bestselling e-learning instructor with over 100,000 โ€ฆ

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Experienced Data Engineering professional with very strong Data Analytics,SQL,Data reporting skills.Experience with Big data technologies Hadoop,Hive and Spark. Can mentor with career, interviews ,growth ,opportunities and any kind of general advise. If you are venturing/starting or planning to move into data engineering role (or moving from a ETL role ), โ€ฆ

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I have 12+ years of working in successful and failed startups with focus on DataEngineering, MachineLearning. I have deep understanding of SaaS products. In last year or so I have focused myself on clean-tech (climate-tech, clean-energy, climate-crisis). I am leading engineering teams and projects for years. I have work experience โ€ฆ

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I am a Data Engineer with several years of experience at companies big and small. I formerly worked at Chime, Zoox (Amazon's self driving company), Instagram, and RocketLawyer. I've done extensive work in all aspects of Data Engineering including the infrastructure and platform side, the pipelining, modeling, and warehousing side, โ€ฆ

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Tips from the Data Engineering blog

Learn more about Data Engineering with our expert advice.

Harnessing the Power of Cloud for Data Engineering and Analytics

Discover the transformative potential of cloud-based data engineering and analytics in our comprehensive guide. Uncover the scalability, cost-efficiency, and cutting-edge innovations offered by cloud platforms like AWS, Azure, and Google Cloud. Embark on a journey to master the skills needed for your next data engineering role.

Want to Transition into a Data Engineering Role? Here's How!

Learn why data engineering is critical for enterprises, explore different roles and responsibilities, and follow a comprehensive learning path to success. This blog post will empower you to unlock the world of data engineering and propel your career to new heights. Don't miss out on this opportunity to become a data engineering expert!

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  • "Naz is an amazing person and a wonderful mentor. She is supportive and knowledgeable with extensive practical experience. Having been a manager at Netflix, she also knows a ton about working with teams at scale. Highly recommended."

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