Senior ML/Data Engineer

Catapult Sports•New York, NY

1d•$157,945 - $259,480

About The Position

Catapult is building the future of sports performance technology with a mission to Unleash the Potential of every athlete and team on earth. Since 2006, our solutions have been leading the way in sports performance software, science, and data. We work with over 5,000+ teams globally, empowering coaches, managers, and trainers in premier teams across various professional leagues. We provide critical information to optimize athletes’ health, game-day readiness, performance, and in-game tactics. Catapult is a sports technology company that empowers professional teams to make data-driven decisions, delivering health, performance, video, and AI insights. We are now building the AI layer that compounds everything Catapult has ever measured, aiming to become the indispensable intelligence partner for every coach and athlete in every sport. This role is the data foundation of that platform, owning the data architecture, feature store, sport knowledge graph, and evaluation framework. This is a high-leverage engineering position in Phase 1 of a platform that will define performance intelligence in professional sport.

Requirements

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, understanding 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: designed schemas for complex relationship networks
Production experience with tenant-level data isolation at the infrastructure level
Comfort working directly with domain scientists and AI engineers; translating data requirements into durable infrastructure

Nice To Haves

Experience with causal inference or counterfactual modeling over graph structures
Background in sports technology, wearable sensor data, or biomechanics data
Experience building knowledge graphs with custom ontologies for a specific domain
Familiarity with LLM evaluation frameworks and their limitations in probabilistic sport science contexts
Experience working with AWS (ECS, EC2, Lambda, SNS, SQS, etc), GraphQL, REST, gRPC, Postgres, Mongo

Responsibilities

Develop and execute strategic workforce plans, coaching senior leaders on organisational design, change management, communication, and talent development to drive engagement, retention, and business performance.
Shape culture and values by identifying organisational needs and implementing impactful, scalable people solutions.
Drive a consistent, high-quality employee experience across the EMEA region, spanning three offices, 16 countries, and multiple employment frameworks.
Provide hands-on support and strategic partnership to leaders, teams, and employees, ensuring people strategies are aligned with business goals.
Partner with the Talent team to deliver strategic initiatives across learning and development, diversity, equity and inclusion, reward, workforce planning, and talent acquisition.
Mentor and lead regional P&C team members, fostering a high-performance culture.
Leverage data and insights to identify trends, inform decision-making, and influence strategic outcomes.