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 and services to ensure timely delivery of high-quality data.
• Design and implement large-scale distributed systems using data processing frameworks like Spark or Flink.
• Create data products that provide features, inference inputs, labels, and reward signals for ML systems.
• Design multi-tenant systems capable of handling high-scale, high-throughput demands while remaining easy to monitor and maintain.
• Implement comprehensive monitoring, logging, and alerting to ensure system observability and proactive issue detection.
• Make data available for self-service and wider integration across the organization.
• Write elegant, maintainable code using JVM languages like Java or Scala and SQL.

What we're looking for

• Proficiency in at least one major JVM stack language (e.g., Java, Scala) and SQL is required.
• Experience building applications using large-scale distributed systems and data processing frameworks like Spark or Flink is required.
• Experience with storage solutions and building high-quality data products is required.
• Knowledge of how ML systems consume data, including features, inference inputs, labels, and reward signals, is required.
• Ability to design multi-tenant systems that handle high-scale, high-throughput demands with strong operational awareness is required.
• Ability to prioritize observability through comprehensive monitoring, logging, and alerting in system designs is required.
• Ability to work in agile environments with vague requirements and provide/receive candid feedback is required.