Ever wondered how Amazon keeps hundreds of fulfillment centers running at peak performance across the globe?
That's where our team comes in.
We build the real-time data platform that gives Amazon's fulfillment network end-to-end visibility — from conveyor belts and robotic systems to software applications and workforce operations.
Think of it as the central nervous system for Amazon's physical logistics: we ingest millions of data points per second from equipment and systems across 100+ facilities worldwide, store years of historical data without sacrificing query speed, and serve it all up through dashboards, APIs, and SDKs that help teams detect problems before they happen, optimize processes in real time, and make smarter decisions about how to move packages faster.
What makes this role different: This isn't a typical web services role.
You'll work at the intersection of physical operations and cloud-scale software — solving problems where hardware unpredictability meets distributed systems challenges.
The data you help collect and serve directly impacts whether a package gets delivered on time, whether equipment gets serviced before it breaks, and whether an entire facility runs smoothly on its busiest day of the year.
You'll own problems end-to-end, from system design through production operations, and your work will be visible in real-world outcomes across Amazon's global logistics network.
Key job responsibilities
You'll design and build distributed systems that operate at massive scale — processing high-velocity time-series data streams, building storage layers that balance performance with cost, and creating APIs that make complex data accessible to thousands of users.
Right now, we're in the middle of a major storage architecture migration, rethinking how we handle hot data to improve reliability and reduce latency.
You'll also have the opportunity to work on data ingestion pipelines that collect signals from industrial hardware, robotics, and software systems — and turn that raw telemetry into actionable insights.