Netflix Interview Process 2026 — Rounds, Tips & Questions

Design a data pipeline to ingest CDC (Change Data Capture) events from a MySQL database into a Snowflake data warehouse in near real-time.

Your RDS MySQL database is becoming a bottleneck. Read queries are slow. How do you scale it on AWS without re-architecting the entire application?

Design Netflix's video recommendation system. Netflix serves 250 million subscribers. How do you generate personalised top-10 rows for each user in real time? Cover: collaborative filtering, content-based signals, contextual signals (time of day, device), and how you handle the cold-start problem for new users.

Design Netflix's adaptive bitrate streaming (ABR) system. How does the client decide which video quality to stream second by second based on available bandwidth? Explain DASH vs HLS, the segment request pipeline, buffer-based rate adaptation algorithms, and CDN architecture.

Design Netflix's content delivery pipeline. A new movie is added. Walk through transcoding into 50+ formats, uploading to CDN edge nodes globally, and ensuring playback starts within 200ms for any device anywhere.

Design Netflix's A/B testing platform. Engineers run 100+ experiments simultaneously on different features. How do you assign users to buckets consistently, collect metrics, measure statistical significance, and avoid interaction effects?

Explain Netflix's Chaos Engineering philosophy and the Simian Army. How do you design a system to be resilient to random instance failures, network partitions, and zone outages? Give a concrete example.

What is the circuit breaker pattern? Explain the three states (Closed, Open, Half-Open), when to trip and reset the breaker, and how Netflix's Hystrix library implements it. When would you NOT use a circuit breaker?

Given a list of movie ratings (1-5 stars) for N users, compute the Pearson correlation between two users to measure taste similarity. Explain how this feeds into collaborative filtering.

Design the video encoding pipeline that takes a raw uploaded file and produces multiple bitrate/resolution variants for adaptive streaming. How do you make this fault-tolerant and cost-efficient at scale?