title: "Data Engineer Interview Questions at Netflix (2026 Guide)" slug: netflix-data-engineer-interview-questions description: "Netflix data engineer interview guide 2026: rounds, Spark/SQL/pipeline questions, system design, and how to prep."
Data Engineer Interview Questions at Netflix (2026 Guide)
Netflix's data engineer interview spans a recruiter screen, a technical screen (SQL plus coding), and a 4-5 round virtual onsite: data modeling, pipeline/system design, coding, and culture. The process runs about 4-6 weeks. Difficulty is high — Netflix operates one of the largest data platforms in the world (petabyte-scale, Spark, Flink, Iceberg — a format Netflix created) and expects candidates who have owned production pipelines at scale, not just written ETL scripts.
Interview Process at a Glance
| Stage | Format | Typical Length | Focus |
|---|---|---|---|
| Recruiter screen | Video | 30 min | Background, platform fit |
| Technical screen | Live | 60 min | SQL + Python coding |
| Onsite: Data modeling | Case | 60 min | Warehouse/lakehouse schema design |
| Onsite: Pipeline design | Case | 60 min | Batch + streaming architecture |
| Onsite: Coding | Live coding | 45-60 min | Python, data structures, Spark |
| Onsite: Culture | Conversation | 45-60 min | Candor, ownership, judgment |
Timeline: 4-6 weeks (estimate). Compensation is top-of-market cash, commonly $300K-$600K+ total (estimate; level and location dependent).
Real-Style Questions by Round
SQL & Coding Screen
- Write SQL for each member's longest consecutive-day viewing streak.
- Given two large tables of playback events and device metadata, find sessions with mismatched region codes.
- In Python, merge k sorted event logs by timestamp with bounded memory.
Data Modeling
- Model the data for "Continue Watching" across profiles and devices.
- Design a fact/dimension schema for content performance reporting by region and cohort.
- How would you handle late-arriving events and schema evolution in an Iceberg table?
Pipeline & System Design
- Design a pipeline ingesting millions of playback events per second into a queryable lakehouse.
- Batch backfill vs. streaming correction — how do you rebuild 90 days of a corrupted metric?
- Design data-quality checks for a table feeding executive dashboards. What pages someone at 3 a.m.?
- Exactly-once semantics: how would you achieve them from Kafka to Iceberg, and what would you give up?
Culture
- Tell me about a pipeline failure that hit downstream consumers. What did you change?
- Describe pushing back on a stakeholder's request for a metric you thought was misleading.
- When did you delete something big — a pipeline, a dataset — and why?
How to Prepare
Know the Netflix data stack: Spark, Flink, Kafka, Iceberg, Presto/Trino. Practice hard analytical SQL (window functions, sessionization) and be ready to defend schema and partitioning choices with numbers. Bring war stories about scale, cost, and data quality.
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FAQs
What tech stack should I know for a Netflix data engineer interview? Spark, Flink, Kafka, Apache Iceberg, and Trino/Presto, plus strong Python and SQL. Netflix created Iceberg — know it.
How hard is the SQL in Netflix data engineer interviews? Hard. Expect window functions, sessionization, and streak problems on billion-row framing, with performance discussion.
Does Netflix ask system design for data engineers? Yes — pipeline architecture at millions of events per second, plus data modeling and data-quality design.
Do Netflix data engineers need streaming experience? Strongly preferred. Most teams run mixed batch/streaming; expect at least one streaming design question.
What is Netflix data engineer compensation? Top-of-market, mostly cash — commonly $300K-$600K+ total (estimate).
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