Data Infrastructure at catapultsports

Compensation

$157,945 – $259,480/yr

Location: New York, New York
Type: Full-time
Level: not_specified
Posted: Jul 28, 2026

Description

Catapult is seeking a passionate Data Engineer specializing in Machine Learning to build the foundational infrastructure for their AI-powered sports performance platform. This role involves owning and developing scalable data architectures, feature stores, sport knowledge graphs, and evaluation frameworks to ensure trustworthiness and reliability of AI-generated insights for coaches and athletes worldwide.

Required Skills

Python
Golang
SQL
Streaming Ingestion
Time-Series Databases
Feature Stores
Graph Database

Additional Information

Required Previous Experiences: 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
Production experience with tenant-level data isolation at the infrastructure level, not just access control
Preferred Qualifications: Experience with causal inference or counterfactual modeling over graph structures
Background in sports technology, wearable sensor data, or biomechanics data, you understand what makes athlete time-series data structurally different from standard telemetry
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