Build high-volume, low-latency Conversion APIs powering Netflix's ads measurement and privacy stack

On Netflix's Ads Identity, Signals and Audiences team, you'll design and build Conversion APIs that ingest consented advertiser engagement events in near-real-time via server-to-server streaming, pixels, and batch, turning them into deduplicated, identity-enriched 'gold' datasets for measurement, retargeting, and reporting — all while staying compliant with global privacy regulation.

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What this interview tests

Conversion API design: server-to-server, batch, and pixel ingestion
Event deduplication, identity resolution, and attribution enrichment
Streaming architectures (Kafka, Flink) at high volume, low latency
Ad tech and privacy/consent regulatory compliance
Cross-functional collaboration across ads, privacy, and legal stakeholders

Common question themes

Design a Conversion API that ingests events from server-to-server, pixel, and batch sources into one 'gold' dataset

How do you handle deduplication and identity enrichment for high-volume conversion events

Walk through a streaming pipeline you built with Kafka or Flink and how you ensured correctness under load

How would you design for consumer privacy and regional ad regulation compliance from the start

Describe a time you had to negotiate priorities across ads, privacy, and business stakeholders

How candidates describe it

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

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