The Data Foundry

Become a Modern Data Architect for the AI and Agentic Era

Qasim Hassan, Ayan Hussain, Abdullah Khan and Haniya Maqsood.

Forty-three chapters across ten parts. Free, open access, and self-paced.

Welcome

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.

Contents

Ten parts

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 and dbt
Part 7 : Real-Time Data, Apache Kafka
Part 8 : AWS for Data Engineers
Part 9 : Azure for Data Engineers

Front matter and appendices sit either side of the ten.

Chapter 1

The Data Engineer's Mindset

You write a script that pulls yesterday's orders from an API and loads them into a database. Twenty lines of Python. You run it once. The rows are there. It works. You move on.

That gap, between code that works and a system you can trust unattended, is what this chapter is about, and it matters more than it used to.

1.1

The Shift You Are Making

The question stops being whether this produces correct output right now, and becomes whether it keeps producing the correct output, automatically, for inputs you have not seen yet, after you have gone home.

Data engineering is about what happens on the second run, the hundredth, and the millionth.

A person trusting bad data eventually notices something feels off. An agent doesn't. It just acts on it.

Chapter 1, on why the standard has risen.

Chapters 2 and 3

The Modern Data Stack

“Just give me a report of yesterday's revenue by region” sounds like a five-minute ask.

Chapter 2 mapped the seven layers of a data platform to the parts of this book. Part 1 starts that journey with SQL, and SQL needs a database engine to run against.

Everything we know about data engineering, written down