Below are books related to data engineering.

Starters and general knowledge:

Other great ones, more specific:

Building the Data Warehouse, Bill InmonData Modeling with Snowflake (Serge Gershkovich), Serge GershkovichThe Data Engineering Cookbook, Andreas KretzData Engineering Patterns on the Cloud, Bartosz KoniecznyIntroduction to Data Engineering, Daniel BeachData With Rust, Karim JeddaData Pipelines Pocket Reference, James DensmoreDAMA-DMBOK: Data Management Body of Knowledge (DAMA-DMBOK)Streaming Systems, Tyler Akidau, Slava Chernyak, Reuven LaxHigh Performance Spark, Holden Karau, Rachel WarrenData Pipelines with Apache AirflowFundamentals of Data Observability, Andy PetrellaScaling Machine Learning with Spark, Adi PolakDeciphering Data Architectures, James Serra (Deciphering Data Architectures (James Serra))Architecture Patterns with PythonLearning Spark, Brooke Wenig, Denny Lee, Tathagata Das, Jules DamjiThe Unified Star Schema. Bill InmonData Engineering Book by Oleg Agapov : Accumulated knowledge and experience in the field of Data EngineeringEnterprise Architecture Fundamentals (Rémy Fannader): Using the Pagoda Blueprint for modeling data architectures with five parts: Take a general perspective on enterprise, systems, and frameworks, technical aspects, and new challenges and technologies.AData Engineering Best Practices: Architect robust and cost-effective data solutions in the cloud era. By Richard J. Schiller, David Larochelle

Design Patterns(Erich Gamma, Richard Helm, October 1994, ISBN-10: 0201633612) - The mother of Design Patterns, general use but not dedicated to Data Engineering.System Design Interview (Alex Xu, Sahn Lam, Volume 2 March 2022, ISBN-10: 0201633612) - This book seems to be a great general approach to designs and patterns, but it doesn’t include Data Engineering.

See also People of Data Engineering, and Data Engineering.

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Created 2023-12-08