Distributed Systems Engineer - Ad Eventing

The Ad Eventing team sits within the Ad Serving & Decisioning org at Netflix Ads. We own the systems that ingest and process billions of ad events per day— from client-side beacons fired during playback to server-side signals from our ad server. Our work spans real‑time event ingestion, deduplication and validation, stream processing pipelines, and the authoritative data contracts that downstream systems (billing, reporting, pacing, ML) depend on.

We operate at the intersection of reliability engineering, data infrastructure, and ads domain expertise.

We are looking for a senior technical leader to own the technical direction of this pod, set the architectural bar, and drive execution on the hardest problems in event processing at Netflix scale. This is a 60% builder / 40% influencer role: you will write code, ship a proof‑of‑concept in your first weeks, and earn the trust of an opinionated senior team while simultaneously setting direction across the organization.

• Own the technical direction of the Ad Eventing team: architecture reviews, incident leadership, capacity planning, and scaling
• Architect and evolve the end‑to‑end ad event pipeline — from client beacon receipt through validation, deduplication, enrichment, and downstream fan‑out — under strict latency and throughput constraints
• Scale our event ingestion infrastructure to handle billions of events per day with high availability, exactly‑once semantics, and sub‑second processing SLAs
• Design and implement robust deduplication and validation systems that ensure event accuracy across retries, network failures, and client‑side inconsistencies
• Build and operate stream processing pipelines (e.g., Kafka, Flink, or equivalent) that power real‑time signals for pacing, frequency capping, and reporting
• Define and maintain authoritative event schemas and data contracts that serve as the source of truth for billing, advertiser reporting, and ML feature pipelines
• Partner closely with Ad Serving, Pacing, Reporting, and Science teams to ensure event data meets the accuracy, latency, and completeness requirements of each consumer
• Drive operational excellence: reliability, observability, deployment automation, capacity planning, and incident leadership across the eventing stack
• Drive modularization and platform‑thinking: build reusable components and clean interfaces that let the team and partner teams move faster

• 10+ years building distributed systems and backend services at large scale; 3+ years in the ads domain
• Deep experience with high‑throughput event ingestion and stream processing at scale — Kafka, Flink, Spark Streaming, or equivalent
• Built and operated event deduplication, validation, and attribution systems in an ads or similarly high‑stakes data environment
• Strong understanding of exactly‑once and at‑least‑once delivery semantics, idempotency patterns, and the trade‑offs between them
• Experience designing event schemas and data contracts that serve multiple downstream consumers with different latency and consistency requirements
• Familiarity with ad measurement concepts: impression tracking, viewability, click attribution, completion rates, and IAB standards
• Track record of technical leadership across multiple teams, setting architectural direction and influencing cross‑functional roadmaps
• Comfortable at the intersection of engineering, data, and product — translating advertiser reporting requirements and billing accuracy needs into production systems
• Demonstrated ability to operate in an environment that is a mix of big‑tech scale and startup speed, delivering production‑ready results on tight timelines

• Experience with CTV‑specific event challenges: server‑side ad insertion (SSAI), VAST/VMAP beacon…