The Data Engineering Cookbook by Andreas Kretz:
Andreas Kertz has written an ebook with research and case studies, codes, podcasts, lectures, case studies, and more. This, in my opinion, is a complete package that will enable anyone to become a data engineer.
And the cherry on top? This ebook is completely free! Yes, you can get started right away. Now is the time to start learning, practising, and preparing for your data engineering career!
Big Data Processing Made Simple by Matei Zaharia
Apache Spark is an analytics engine for Big Data and machine learning. Spark has APIs in Java, Scala, Python, and R, and this book shows you how to use Spark in a variety of business and organizational scenarios.
Despite its narrow emphasis, this is a good book to read for anyone interested in a data engineering or data science profession that requires working with Spark.
The Data Warehouse Toolkit by Ralph Kimball:
The third edition of this book provides a complete library of updated dimensional modelling techniques, the most comprehensive collection ever. It incorporates new and improved star schema dimensional modelling patterns, two new chapters on ETL approaches, new and enlarged business matrix for 12 case studies, and other new and improved features.