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The Ultimate Data Engineering Interview Playbook 2026: 200+ Real Questions Covering ETL Pipelines, SQL at Scale, Cloud Platforms, and System Design fr
Paperback
Series: The Complete Tech Interview, Book 2
CareersGeneral ComputersProgramming
Publisher: Independently Published
Published: May 29 2026
Pages: 328
Weight: 1.25
Height: 0.69 Width: 7.50 Depth: 9.25
Language: English
SQL interviews at data science companies test statistics and product sense. Data engineering interviews test something different - whether you can design distributed pipelines that don't break, model data at a scale that makes analysts fast, reason about streaming versus batch trade-offs under pressure, and communicate architectural decisions to people who depend on the infrastructure you build.
Most interview preparation resources treat data engineering as a chapter in a data science book. This playbook treats it as the discipline it actually is - with its own interview format, its own technical depth requirements, and its own career trajectory.
What's Inside- 200+ real questions from FAANG, top startups, and Wall Street - with full answer frameworks for every one
- SQL at scale - window functions, query optimization, partitioning strategies, and petabyte-scale patterns that warehouse interviews actually test
- Python and PySpark - data transformation logic, Spark optimization, skew handling, and the production patterns interviewers probe at senior levels
- ETL and ELT pipeline design - idempotency, atomicity, CDC, late data handling, backfill strategies, and failure recovery
- Apache Kafka and stream processing - topics, partitions, delivery semantics, Flink versus Spark Structured Streaming, and real-time pipeline design
- Workflow orchestration - Airflow DAG design, production failure modes, Prefect and Dagster compared
- Cloud platforms - BigQuery, Snowflake, Redshift, and Databricks at the optimization depth interviews require
- Data modeling - dimensional modeling, slowly changing dimensions, Data Vault, and schema design for analytical workloads
- Data quality and observability - data contracts, lineage, Great Expectations, dbt tests, and monitoring strategies
- System design - the five-stage framework with three complete walkthroughs: real-time analytics platform, ML data infrastructure, and lakehouse migration
- AI and ML integration - feature stores, embedding pipelines, RAG architecture, and vector databases
- Senior and staff strategy - technical leadership, organizational influence, and salary negotiation
This playbook is written for the analyst or data scientist transitioning into data engineering, the working data engineer targeting a step up at a better company, and the international candidate preparing for a FAANG data engineering loop - everyone who needs to translate genuine technical skill into interview-winning performance.
The only data engineering interview book I found that actually covers what 2026 interviews test. The system design walkthroughs alone are worth the price.
I used this to prep for my Databricks loop. The pipeline design and Kafka chapters are the most thorough treatment I've seen outside of internal documentation.
Book 2 of The Complete Tech Interview Series. If you have a data engineering interview in the next 90 days - this is the book you need.Also from
Moss, Amon
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