Data Engineering for Beginners by Chisom Nwokwu - Book Retelling Series
I picked up “Data Engineering for Beginners” by Chisom Nwokwu (Wiley, 2026, ISBN: 9781394325412) a few weeks ago. I was looking for something that explains data engineering from scratch, without assuming you already know half the field. This book does exactly that.
Here’s what I found: a 13-chapter guide that starts with “what even is data” and ends with career advice and interview prep. It’s written like a roadmap. You can read it front to back, or jump to whatever chapter you need.
About the Author
Chisom Nwokwu is a software engineer who has worked at Microsoft and Bank of America. She was also nominated as a Rising Star by the Women Tech Network. She wrote this book because she remembers how hard it was to break into data engineering without a clear starting point. She started a software engineering role in 2021 that required building and managing data platforms, and she had almost no background in data at the time. That experience of struggling through the basics and eventually figuring things out is what shaped the book.
I respect that. The best technical books come from people who remember what it felt like to not know things.
What the Book Covers
The book has 13 chapters, plus an appendix with interview questions and a glossary. Here’s the quick rundown:
Understanding Data - what data actually is, its history, the different types (structured, semi-structured, unstructured), and why it matters across industries.
Introduction to Data Engineering - what data engineers do, the data engineering lifecycle, and how to work with stakeholders.
Database Fundamentals - relational vs NoSQL databases, when to use each, and the ACID principles.
SQL Fundamentals - from basic queries to subqueries and window functions. Hands-on stuff.
Database Design - data modeling, entity relationship diagrams, normalization, and when to break the rules with denormalization.
Data Warehouses, Data Lakes, and Data Lakehouses - storage at scale, star and snowflake schemas, data marts.
Data Pipelines - batch vs streaming, windowing, Lambda architecture, orchestration, and automation.
Data Quality - what causes bad data and what it costs you.
Data Security - authentication, authorization, encryption, data masking.
Data Governance - policies, processes, regulations, and keeping data managed responsibly.
Big Data and Distributed Systems - the 5 V’s, Apache Spark, Hadoop.
Data Engineering on the Cloud - IaaS, PaaS, SaaS, cloud storage types, compute services.
Building a Career in Data Engineering - roles, interviews, career planning.
That’s a solid spread. It covers the full spectrum from “what is a row in a table” to “how do I design a distributed system on the cloud.”
Who Is This Book For?
The author wrote it for three groups of people:
- Complete beginners who want a starting point that doesn’t feel like a textbook.
- Tech-adjacent folks like software engineers, data analysts, and AI engineers who keep hearing about data engineering but don’t fully understand it.
- Career switchers coming from outside tech who want a practical path into the data world.
I would add a fourth group: people like me who have been in IT for decades but want a clean, modern summary of how data engineering fits together today. Sometimes you just want someone to lay it all out in order, and this book does that.
What to Expect from This Series
I’m going to walk through each chapter and give you my take on it. Not a summary, not a copy. My retelling. The stuff I found useful, the parts that made me think, and the occasional “here’s how this connects to the real world” commentary from someone who has been around computers since before some of you were born.
This will be 18 posts total. Some chapters get split into two posts because there’s a lot to cover. I’ll keep each one short enough to read with your morning coffee.
If you’re thinking about getting into data engineering, or you just want to understand what the data team at your company actually does, stick around. This is a good book and I think you’ll get something out of it.
Let’s get started.
This is part 1 of 18 in my retelling of “Data Engineering for Beginners” by Chisom Nwokwu. See all posts in this series.
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