Data Engineering with Google Cloud Platform: A Book Retelling Series

I just finished reading “Data Engineering with Google Cloud Platform” by Adi Wijaya (2nd edition, Packt Publishing, 2024) and I want to share what I learned. Not as a dry summary, but more like telling a friend what the book is about over coffee.

ISBN: 978-1-83508-011-5

Why This Book

If you’re trying to break into data engineering or you already work with data but want to learn Google Cloud, this book is a solid starting point. Adi Wijaya is a cloud data engineer at Google with over a decade of experience, and he writes like someone who actually builds stuff, not like someone who just reads documentation.

The second edition came out in April 2024, so the content is pretty fresh. It covers everything from “what is data engineering” basics all the way to CI/CD pipelines and career advice.

What I’ll Cover

I’m breaking this into a series of posts, one chapter at a time. Some bigger chapters get split into two parts because there’s just too much to cover in one sitting.

Here’s the roadmap:

Part 1: Getting Started

• Chapter 1: What Is Data Engineering Anyway?
• Chapter 2: Getting Started with Google Cloud for Big Data

Part 2: Building Things

• Chapter 3: BigQuery Data Warehouse (2 parts)
• Chapter 4: Cloud Composer Workflows (2 parts)
• Chapter 5: Data Lake with Dataproc (2 parts)
• Chapter 6: Streaming with Pub/Sub and Dataflow (2 parts)
• Chapter 7: Visualizing Data with Looker Studio
• Chapter 8: Machine Learning on GCP (2 parts)

Part 3: Strategy and Architecture

• Chapter 9: User and Project Management
• Chapter 10: Data Governance (2 parts)
• Chapter 11: Cost Strategy
• Chapter 12: CI/CD for Data Engineers (2 parts)
• Chapter 13: Growing as a Data Engineer (2 parts)

Who This Is For

You don’t need to be a data engineer to follow along. If you’re curious about how companies handle large amounts of data using Google Cloud, you’ll get something out of this. But if you’re already working with data and want to level up your GCP skills, even better.

The book assumes some basic SQL and Python knowledge, but I’ll keep these posts focused on concepts rather than code.

My Take So Far

What I like about this book is that it doesn’t just list features. It walks you through building actual data pipelines, step by step. You start with fundamentals, move to hands-on building, and finish with the strategic stuff that makes you better at the job, not just better at the tools.

Let’s get into it. First up: the fundamentals of data engineering.

This is part of my retelling of “Data Engineering with Google Cloud Platform” by Adi Wijaya (2nd edition, Packt, 2024). Follow along with the full series using the data-engineering-gcp tag.