Netflix Interview Question Bank
Netflix's current engineering loop is high-signal and repeat-heavy: Ads candidates see the same topo / frequency-cap / ads data-modeling trio, Member-Commerce-Games candidates see homepage dedupe and duplicate-detection variants, and Infra / Data Platform candidates see cache, latency, and concurrency rounds. The technical prompts are usually solvable, but the grading is communication-heavy: candidates are expected to clarify vague requirements, write tests, explain trade-offs, and connect their past work tightly to the target org.
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Key-Value Store with TTLDesign a Non-Repeating Movie Playlist with Score UpdatesTime Limited CacheSparse Matrix MultiplicationKey-Value Cache with Per-Entry ExpirationFastest Broadcast Path to All CitiesTimed Cache with Expiration and OOM EvictionReport Each Binary-Tree Node's Level and Balance StatusMaximum Overlap Among Closed IntervalsCount Pairs of Strings with No Common CharactersLongest Substring Without Repeating CharactersLongest Run of Identical CharactersTimed Cache with TTL and LRU EvictionMinimum Time to Finish All Dependent Tasks with Durations (Detect Cycles)Topological Sort (Directed Graph Ordering)DFS: Print Each Node's Level and Whether It Is BalancedDesign a TTL Cache (cache with time limit)Design a word counter for streaming textThread-safe Sliding Window P99 Latency TrackerWeighted Cache Eviction (Weight-Constrained Cache)Topological Sort / Dependency ResolutionCommand Executor with Execute and UndoTopological SortJSON Path Query on Map<String, Object> with Wildcard (*)Inverted Index with Phrase SearchImplement an Atomic Counter (Thread-Safe Counter)Double-Checked Locking / Locking Correctness in Multithreaded CodeDesign a Weighted Cache (Phone Screen)Rotating Top-Scored Title Service (Upsert + GetTop with No-Immediate-Repeat)Count Pairs of Show Names Sharing No Common Characters