SWE5 building large-scale advertiser audience onboarding and activation pipelines for Netflix Ads

Netflix's Ads Audience Activation team ingests advertiser custom audiences and conversion events and builds retargeting audiences from engagement/conversion signals. The role centers on scalable batch and streaming data pipelines (Kafka, Flink, Spark) for third-party advertiser signal ingestion feeding targeting, measurement, and optimization systems. Netflix's SWE5 title plus a $388K-$619K range signal a senior-to-staff bar; expect deep systems-design and distributed-data-engineering questions, not general full-stack.

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What this interview tests

Streaming event architecture design (Kafka, Flink)
Batch + streaming data onboarding/activation systems for advertiser audiences
Large-scale distributed data processing (Spark) at high throughput/low latency
Ads regulation, data-sharing compliance, and privacy considerations
Cross-team collaboration with targeting/measurement/optimization consumers

Common question themes

Design a system to ingest third-party advertiser custom audience data and activate it for retargeting

How would you architect a streaming pipeline with Kafka/Flink for conversion event processing at scale

Tell me about handling data at extremely large volume — what broke and how did you fix it

How do you think about ads data privacy/compliance when onboarding advertiser signals

Describe a time you had to negotiate priorities or influence a cross-functional partner team

How candidates describe it

Real Software Engineer 5 - Ads Audience Activation interview stories — retold from candidates' public write-ups, with sources.

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