Interview
Data Engineer Interview Playbook
How data engineering interviews run, what each round tests, and how to prepare.
- Handwritten-style
- Diagrams and tables
- Worked examples
Who this notebook is for
Candidates preparing for a full data engineering interview loop, from the first screen to the senior and staff rounds.
What you will be able to do
- Know the stages of a loop and what each interviewer is scoring
- Tell behavioral stories with the STAR method
- Do back-of-envelope estimates for storage, throughput and cost
- Run a system design answer, a debugging round and a salary conversation
What's inside
Pick a chapter and the notebook opens right there.
- Interview Loop Anatomy & LevelsThe 5 standard evaluation loops (recruiter, technical screen, SQL/coding, system design, behavioral/bar-raiser), leveling expectations (DE1, DE2, Senior, Staff), calibrated scoring rubrics & 12-week preparation timelineStart here
- Behavioral Mastery & STAR MethodThe STAR+L storytelling framework, 20 essential DE behavioral stories, full worked answers for production outages, executive pushback, contract negotiations & Amazon/Meta leadership principlesStart here
- Back-of-Envelope EstimationLatency numbers every DE must know, throughput & QPS math, daily storage sizing formulas, cluster/partition sizing rules, cloud FinOps cost calculations & 2 end-to-end worked estimation drillsStart here
- System Design Framework & 10 Full Architectures45-minute 4-phase timeboxing strategy, 10 production designs (clickstream, CDC lakehouse, financial ledger, real-time analytics, ML feature store, DW migration, IoT telemetry, ad attribution, search indexing, data mesh) & scoring rubricsStart here
- SQL & Coding Interview StrategyWindow functions, gaps and islands, retention cohorts, sessionization, deduplication, hierarchical CTEs, Python generator streams, memory profiling, sliding windows & 20 timed problem drillsStart here
- Pipeline Debugging & Incident Triage4-phase incident framework (triage, isolate, mitigate, RCA), step-by-step triage scripts for Spark 99% hang/skew, silent data corruption, Kafka lag explosion, cloud cost runaway & blameless post-mortem templatesStart here
- Technology Trade-Off QuestionsDeep multi-dimensional comparative matrices (Kafka vs Kinesis vs Pub/Sub, Spark vs Flink vs DuckDB, Delta Lake vs Iceberg vs Hudi, Snowflake vs Databricks vs BigQuery, Airflow vs Dagster vs Prefect)Start here
- Leadership, Staff-Level Strategy & GovernanceThe 4 Staff archetypes, data roadmapping, build vs buy ROI framework, enterprise data governance (RBAC, column masking, GDPR right-to-be-forgotten), influencing without authority & team topologyStart here
- Negotiation, Resume & Portfolio StrategyQuantified resume bullets, open source portfolio architectures, inbound LinkedIn recruiter funnel, total compensation teardowns (base, RSUs, sign-on), counter-offer scripts & reverse interview questionsStart here
- Mock Interview Rounds, 7-Day Plan & Cheat Sheet3 verbatim mock interview transcripts (Staff design, live incident triage, executive behavioral), 7-day final cramming protocol & two-page master reference cheat sheet of formulas and rulesStart here
Practice this
Put it to work on LakeBench.
Read the guide first
Short explainers that pair with this notebook.
Common questions
- Which levels is it written for?
- It covers expectations from entry level to senior and staff, so you can see what changes as the role gets bigger.
- Does it replace practising problems?
- No. It teaches how to approach each round. Pair it with the SQL, Python and system design practice on LakeBench.
- Can I read a sample before I commit?
- Yes. The contents pages and the first pages of every notebook can be read online, so you can judge the style before going further.
