The Data Engineering Interview Playbook
You know SQL. You know Python. You have built pipelines that run in production. And you still walk out of a data engineering interview not sure what went wrong. That is not a skills problem. Interviews test a narrow, specific set of things: how you reason out loud under a time limit, how you defend a design decision you just made up on the spot, how you turn a vague take-home prompt into a project a stranger will judge you on. Nobody teaches that on the job, and most interview prep material is written for software engineers, not for the SQL screen, the pipeline round, or the "walk me through your data model" conversation that data engineering interviews actually run on. This book is that missing round-by-round playbook. Seven chapters, 150 pages, built specifically around the loop a data engineer actually goes through: the SQL round, the pipeline and coding round, system design, the take-home project, the behavioural round, and the closing "do you have any questions for us?" round, plus a primer chapter if your SQL fundamentals need a refresh first. By the time you finish it, you will have: - Worked through 18 SQL interview problems and 12 Python pipeline problems yourself, not just read the solutions - A repeatable way to reason through a system design question out loud instead of memorising diagrams - A finished take-home project you can study against an actual grading rubric, before you get handed your own prompt - Your own STAR-shaped stories written down for the behavioural round, before you are sitting in the room needing them - A real answer ready for "do you have any questions for us," instead of the silence that usually follows it Table of contents: - Chapter 0: SQL concepts primer, the fundamentals the rest of the book assumes you already have - Chapter 1: The SQL round, 18 practice problems with full solutions and reasoning - Chapter 2: The pipeline and coding round, Python problems on cleaning, dedup and idempotency - Chapter 3: Data modelling and system design - Chapter 4: The take-home project rubric, with a full runnable example project - Chapter 5: The behavioural round - Chapter 6: Questions to ask them What makes it different: Every SQL query and every Python function in this book was actually run against real data before it was printed. The output shown under each one is the real output, not a description of what it should return. It is also deliberately tool agnostic. No PySpark syntax, no Airflow DAGs. Just the fundamentals an interviewer is actually checking for underneath whatever stack they use, so what you learn here works whether the job runs on Spark, dbt, Kafka, or something that has not been invented yet. Included with the book: a companion folder of runnable .sql and .py files for every problem, so you can execute the code yourself instead of retyping it from a PDF. Written by stackagen, a data and AI engineer with seven-plus years of experience, including work on high-stakes systems in banking, equities and order processing.
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