The Data Foundry
Master data engineering from foundations to cloud.
This book is organized as a complete learning path for modern data engineering. It starts with the mindset and systems view of the profession, then builds through SQL, Python, orchestration, engineering practices, AI-assisted workflows, cloud warehousing, streaming, AWS, and Azure.
Book Path
- Front Matter
- Part 0 - Thinking Like a Data Engineer
- Part 1 - SQL: The Language of Data
- Part 2 - Python: The Engineer's Tool
- Part 3 - Orchestration: Apache Airflow
- Part 4 - Engineering Practices
- Part 5 - Agentic Data Engineering
- Part 6 - Cloud Warehousing: Snowflake + dbt
- Part 7 - Real-Time Data: Apache Kafka
- Part 8 - AWS for Data Engineers
- Part 9 - Azure for Data Engineers
- Appendices
How to Use This Book
Read the parts in order if you are building from foundations. If you already work with data systems, use the sidebar as a reference map and jump to the chapters that match your current project.
Each chapter page is structured to grow into a full lesson with concepts, examples, pitfalls, exercises, and production context.