Senior ML/Data Engineer

Catapult is building the future of sports performance technology, with a mission to Unleash the Potential of every athlete and team on earth. We don't just work in the sporting industry; we are actively changing it. Since 2006, our solutions have been leading the way in sports performance software, science, and data, in a world where 1% can literally mean the difference between winning and losing. We work with over 5,000+ teams around the world, empowering coaches, managers and trainers in premier teams in the NFL, NBA, NHL, MLS, EPL, AFL, NRL, NCAA and more. We provide the information they need to optimize athletes’ health, game-day readiness, and performance, as well as in-game tactics. Catapult is a sports technology company that empowers professional teams to make data-driven decisions. We deliver health, performance, video, and AI insights from the locker room to competitive environments, ensuring every decision is an opportunity to gain an advantage, sharpen performance, and build lasting success. WE WANT PEOPLE WHO ARE PASSIONATE ABOUT MACHINE LEARNING Catapult Sports is the global leader in athlete performance technology, trusted by elite clubs and national programs across every major sport on every continent. Our hardware and software platforms are on the training ground and in the arena with the best teams in the world — and we have been there, continuously, for over two decades. We are now building the AI layer that compounds everything Catapult has ever measured. The goal is ambitious: to become the indispensable intelligence partner for every coach and athlete in every sport — a system that connects the full depth of performance data and surfaces the right insight at the right moment, with the confidence to act on it. This role is the data foundation of that platform. You will own the infrastructure every AI agent reasons over: the data architecture, the feature store, the sport knowledge graph, and the evaluation framework that makes every recommendation trustworthy before it reaches a practitioner. This is not a support role or a pipeline maintenance job. It is the highest-leverage engineering position in Phase 1 of a platform that will define what performance intelligence means in professional sport. If you have built data infrastructure at scale — time-series, feature serving, graph — and you care deeply about whether the systems you build are actually trustworthy, not just functional, this is the role that will define your next chapter. WHAT YOU’LL DO You will own the data infrastructure that every AI agent on the platform reasons over. That means designing and building the systems that ingest, store, and serve athlete performance data at scale — from real-time sensor streams to longitudinal historical records — and ensuring every layer is governed, isolated per client, and trustworthy at the moment of a high-stakes decision. You will build the feature store that makes derived metrics available to agents in milliseconds, design the sport knowledge graph that encodes relationships between athletes, loads, injuries, and outcomes, and create the evaluation framework that validates every agent’s recommendations against the full distribution of real-world cases before any output reaches a practitioner. You will work directly with domain scientists and AI engineers, translating deep sport science requirements into durable, production-grade infrastructure that compounds in value with every season of data added to the platform. WHAT YOU’LL NEED NON-NEGOTIABLE 5+ years of production data engineering at scale, time-series databases, data lakes, feature stores in a real-time or near-real-time environment Experience building probabilistic evaluation frameworks or model calibration infrastructure, you understand the difference between a model that works and a model that is trustworthy Strong Python, Golang and SQL; experience with streaming ingestion (not batch-only) for live sensor or IoT data Graph database experience:…