Distributed Systems Engineer L5, Commerce Insights and Data Products Engineering

What you'll do

• Build low-latency data products to power algorithms and machine learning models for commerce and identity flows.
• Develop highly available and reliable distributed data systems to ensure timely delivery of high-quality data.
• Design multi-tenant systems capable of handling high-scale, high-throughput demands while remaining easy to monitor and maintain.
• Implement batch and real-time data processing using frameworks like Spark or Flink.
• Create scalable infrastructure that provides self-service data access for wider integration across the company.
• Integrate observability features including comprehensive monitoring, logging, and alerting into all system designs.
• Translate business needs into technical solutions to optimize product experiences for Netflix members.

What we're looking for

• Proficiency in at least one major JVM stack language such as Java or Scala is required.
• Proficiency in SQL (any variant) is required.
• Experience building applications using large-scale distributed systems and data processing frameworks like Spark or Flink is required.
• Experience with various storage solutions for high-quality data delivery is required.
• Knowledge of how machine learning systems consume data, including features, inference inputs, labels, and reward signals, is required.
• Ability to design multi-tenant systems that handle high-scale and high-throughput demands while being easy to monitor and maintain.
• Strong operational awareness and a focus on observability through monitoring, logging, and alerting is required.
• Ability to work in agile environments with vague requirements and provide candid feedback in a collaborative setting.