Netflix Kafka Interview Questions 2026
Published July 22, 2026 · Updated July 22, 2026
5 real Kafka interview questions asked at Netflix. Upvoted by engineers who cleared the loop. Covers System Design, Technical rounds.
5 questions
293 engineers asked
377 upvotes
Company: Netflix
Technology: Kafka
All Kafka Questions Asked at Netflix
Netflix
Hard
System Design round
Distributed SystemsKafkaAWS
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.
↑ 95 upvotes · 93 engineers asked this · SDE2
Netflix
Hard
System Design round
Distributed SystemsAWSKafka
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.
↑ 69 upvotes · 46 engineers asked this · SDE2
Netflix
Hard
System Design round
Distributed SystemsKafkaAWS
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?
↑ 62 upvotes · 40 engineers asked this · SDE2
Netflix
Hard
System Design round
5–8 YearsPythonKafkaSnowflake
Design a data pipeline to ingest CDC (Change Data Capture) events from a MySQL database into a Snowflake data warehouse in near real-time.
↑ 131 upvotes · 103 engineers asked this · Data Engineer
Netflix
Medium
Technical round
3-6 yearsKafka
Kafka topics have a retention period, but consumer offsets also have their own retention. What happens if a consumer group is offline longer than the offset retention period?
↑ 20 upvotes · 11 engineers asked this · Senior SDE
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Frequently asked questions
Design Netflix's video recommendation system.
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 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 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?
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?
Design a data pipeline to ingest CDC (Change Data Capture) events from a MySQL database into a Snowflake data warehouse in near real-time.
Design a data pipeline to ingest CDC (Change Data Capture) events from a MySQL database into a Snowflake data warehouse in near real-time.
Kafka topics have a retention period, but consumer offsets also have their own retention. What happens if a consumer group is offline longer than the offset retention period?
Kafka topics have a retention period, but consumer offsets also have their own retention. What happens if a consumer group is offline longer than the offset retention period?