Data engineering interviews rarely stop at definitions.
The interviewer changes a requirement, introduces late data, or asks what happens after a job writes half a batch and fails.
Think Like a Data Engineer is written for engineers with roughly one to five years of experience who want to answer those questions with a clear line of reasoning.
The book follows one fictional online marketplace as its data platform grows from nightly CSV files into dependable batch and streaming systems. Across 100 technical questions, it covers SQL, Python, data modelling, storage formats, incremental ingestion, orchestration, data quality, distributed processing, streaming, reliability, and system design.
Every question explains what to clarify, how to structure the reasoning, which trade-offs matter, and what an acceptable answer might sound like. The book trains you to work from requirements, grain, scale, failure modes, and recovery instead of memorising one perfect response.
The material is cloud-agnostic and country-agnostic. Familiar technologies appear as examples, while the engineering ideas remain portable.
Use the book chapter by chapter, as a quick reference before an interview, or as a set of mock questions to answer aloud.
"synopsis" may belong to another edition of this title.
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