Netflix data engineering interview questions lean harder on production-DE patterns than the typical FAANG SQL/algorithm loop. Expect SQL problems built around window functions ( LAG , LEAD , PARTITION BY ), anti-joins , set operations , relational division , and time-series date logic—and Python problems that read like real pipeline code: monotonic stacks for span queries, sliding windows for streak detection, deque rolling buffers for fixed-memory streams, and resumable ETL with checkpoint files .

This guide walks through the eight topic clusters Netflix actually tests, each with a detailed topic explanation , per-sub-topic explanation with a worked example and its solution , and an interview-style problem with a full solution that explains why it works.…