Claude, Gemini) daily to accelerate implementation, testing, and debugging - continually validating every result for correctness, privacy, and cost Collaborate with a team of world-class engineers and product managers; grow through code and design reviews, and mentor others as you gain seniority Contribute to on-call, monitoring, and continuous reliability and efficiency improvements; more senior engineers help lead incident response and root-cause analysis Work effectively in a rapidly changing, sprint-based Agile environment, and contribute to a culture that emphasizes reliability, resiliency, extensibility, scalability, and productivity. Engineer secure, scalable data and machine learning systems across real-time, near-real-time, and batch execution contexts using Spark, Kafka, Iceberg, and beyond Own the design and delivery of core components - from pipeline architecture to ML model development, training, and deployment - including support for privacy-preserving, mission-critical infrastructure Drive reliability, performance, and efficiency improvements across your systems, including schema changes, backfills, and the experimentation and testing infrastructure (e.g.