How to Get Started with Data Engineering

Whether you work in a different field or are curious about what Data Engineering is, this is the right place to start as a data engineer.

First, you need to get a short overview of What is Data Engineering, and then read the trilogy of the defined articles that started the field by Maxime, starting with The Rise of the Data Engineer.

Then it really depends on what your role as a data engineer is. Are you doing more platform work, more Business Intelligence work, or Data Analytics, or even Software Engineering? All of these do slightly different work and require different skills.

The typical toolbox of a data engineer can be found Data Engineering Toolkit (including a 3-weeks roadmap), and the most important concepts are at Data Engineering Concepts:

• If you prefer a top-down approachthat introduces you to the field, the history of data engineering, and its challenges, check out my book, with the chapter Introduction to the Field of Data Engineering, and continue with the rest of the chapters.
• If you like a bottom-up approachand already have some knowledge, but want to learn more and see where your curiosity leads you, definitely check out my Data Engineering Vault as part of my Second Brain. You can search and click through backlinks and outgoing links, or use the interactive graph provided that links to the relevant blog articles or book chapters.
• Of if you like hands-on projects, check out the Open-Source Data Engineering Projects.

I think if you don’t like being the center of attention, prefer working in the background, enjoy problem-solving all day, want to keep up with the latest, and like data, then it’s still a very good path.

Surely it’s hard to say what happens with AI, so maybe instead of focusing too much on learning as many programming languages (still learn one programming language) or details, focus on the principles, the Data Engineering Fundamentals.

For more links to start, you can find some of my maps of content notes, which provide you with many more links and other platforms to learn from, with curated, up-to-date lists for each category:

• Books of Data Engineering: A selection of essential reads for every data engineer.
• People of Data Engineering: Learn from the pioneers and current leaders shaping the data engineering landscape.
• Data Engineering Glossaries & Handbooks: Glossaries and Handbooks that explain the complex terms of DE.
• RSS feeds for Data Engineering: My list of best data engineering blog posts as RSS feeds.
• Data Engineering Whitepapers: Whitepapers that define the foundation of data engineering.
• Data Engineering Blogs and Newsletters: Providing insightful articles, podcasts, and newsletters on DE.
• Data Engineering YouTube: Popular YouTube Channels focusing on DE.
• Learning Data Engineering: With more resources, such as hands-on projects, courses, and boot camps, to start learning.

I hope that helps. If anything is missing or you’d like to know more, reach out or follow along at my newsletter. Subscribe directly here.

Origin: Data Engineering