best 10 data engineering books in 2025
Looking to upgrade your skills with the best data engineering books in 2025? Whether you're a beginner starting your journey or an experienced engineer refining your expertise, our top 10 picks cover everything from building data pipelines and managing ETL workflows to mastering cloud platforms and modern data architectures. These books are trusted by industry professionals and reflect the latest trends and tools in data engineering. Explore practical guides, hands-on tutorials, and advanced strategies—all carefully selected to help you stay competitive in the fast-paced world of data.
Fundamentals of Data Engineering
Plan and Build Robust Data Systems 1st Edition, Kindle Edition by Joe Reis (Author), Matt Housley (Author)
Docker Deep Dive
Zero to Docker in a single book Kindle Edition by Nigel Poulton (Author)
Data Engineering Excellence
Architecting Resilient Systems from Scratch to Scale (The Innovators of AI and Data Series Book 3) by Kai W. Calder (Author), Starforge Publishing (Author)
Data Engineering with Python
Work with massive datasets to design data models and automate data pipelines using Python Kindle Edition by Paul Crickard III (Author)
Data Engineering Best Practices
Architect robust and cost-effective data solutions in the cloud era 1st Edition, by Richard J. Schiller (Author), David Larochelle (Author)
Hadoop
The Definitive Guide: Storage and Analysis at Internet Scale 4th Edition, by Tom White (Author)
Spark
The Definitive Guide: Big Data Processing Made Simple 1st Edition, by Bill Chambers (Author), Matei Zaharia (Author)
Data Pipelines Pocket Reference
Moving and Processing Data for Analytics 1st Edition by James Densmore (Author)
Make Your Own Neural Network
Financial Data Engineering: Design and Build Data-Driven Financial Products 1st Edition, Kindle Edition by Tamer Khraisha (Author)
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