Netflix is a company dedicated to entertaining the world through innovative storytelling and technology. The Senior Software Engineer in the Analysis team will design, build, and operate analysis tooling to enhance A/B test analysis and ensure the reliability and performance of these systems.
Responsibilities:
- Build and evolve critical experiment analysis tooling
- Build, maintain, and improve real-time and batch analysis workflows for experiment analysis, regression detection, and more
- Own reliability and performance
- Participate in on-call, lead incident response, and drive long-term reliability improvements
- Instrument services with rich observability (metrics, logs, traces) and continuously tune for resilience, performance, and scalability
- Shape data and integration surfaces
- Collaborate with teams using technologies like Flink, Spark, Elasticsearch, and Druid to ensure experimentation data is correct, timely, and usable
- Define clear data and API contracts for consumers and pipelines
- Partner with product engineering teams
- Deeply understand experimentation workflows across Netflix
- Simplify and improve the experience for monitoring and deciding experiments
Requirements:
- Strong understanding of experimentation lifecycle and risks
- You've done it before: run or facilitated experiments with large business implications, understanding the risks and rewards of experimentation at scale
- A background in data science/statistics is a big plus
- Backend & distributed systems depth
- You've built and operated reliable and observable backend workflows and understand how to apply core algorithms, and systems design to real-world distributed systems
- Strong coding & operational rigor
- You write high-quality code and systems, and have owned production services end-to-end: monitoring, on-call, debugging, and systematic performance and reliability improvements
- High-impact collaboration & product sense
- You work effectively with other engineers and cross-functional partners, bring clarity to ambiguity, drive decisions, and keep a sharp focus on delivering value to internal users and stakeholders