Senior ML & Data Engineer — Sports Performance Intelligence

Catapult; New York (NY); On-site; USD 158,000 - 259,000; Full time

Benefits offered by this job

Health, Dental, Vision

401(k) retirement plan

Paid leave & holidays

Job summary

Catapult is seeking a Senior ML / Data Engineer to build the data infrastructure powering its performance intelligence platform. You will own production data pipelines for high‑volume time-series and real‑time ingestion, design scalable storage, and enable ML features with low latency.

You will collaborate with data scientists, ML engineers, and sport scientists to deliver durable, multi‑tenant systems and robust observability across a global customer base.

Qualifications

• 5+ years of full-time professional software or data engineering experience.
• Proven experience designing, building, and operating production data infrastructure at scale.
• Strong experience with time-series data or time-series databases (InfluxDB, TimescaleDB, Prometheus, ClickHouse, etc.).
• Significant experience with real-time or streaming data ingestion (Kafka, Kinesis, Flink, Spark Streaming, Pulsar).
• Experience designing graph data models or graph schemas.
• Experience operating multi-tenant systems with tenant-level data isolation.
• Strong Python and SQL skills; Go desired.
• Experience with production systems emphasizing reliability, scalability, observability, and data correctness.
• Ability to own ambiguous technical problems and translate into practical architectures.
• Experience with data scientists/ML engineers and domain specialists.
• Experience with causal inference, counterfactual modelling, or simulation.
• Experience with wearable sensors, IoT data, biomechanics, or sports tech.

Responsibilities

• Design and build production data infrastructure for high-volume athlete performance and sensor data.
• Build and operate real-time and near-real-time ingestion systems for streaming data.
• Design storage and data architectures for high-volume time-series data and longitudinal athlete records.
• Enable production features and derived metrics for ML systems with low latency.
• Design graph data models and schemas representing relationships between athletes, training loads, injuries, performance, and outcomes.
• Build ML evaluation infrastructure to measure model reliability and calibration across real-world cases.
• Maintain strong tenant-level data isolation across clubs and customers.
• Establish data provenance, lineage, auditability, and observability across the platform.
• Collaborate with ML/AI engineers to provide reliable data foundations for training, inference, and evaluation.
• Work with sport scientists and domain experts to translate requirements into durable production systems.
• Make pragmatic technology and architecture decisions as the platform evolves.

Skills

Time-series DBs

Production infra

Python

SQL

Go

Streaming tech

Graph models

Multi-tenant

Data provenance

ML collaboration

Tools

Kafka

Kinesis

Flink

Spark Streaming

Pulsar

Postgres

MongoDB

REST/GraphQL

Job description

Catapult is seeking a Senior ML / Data Engineer to build the data infrastructure powering its performance intelligence platform. You will own production data pipelines for high‑volume time-series and real‑time ingestion, design scalable storage, and enable ML features with low latency.

You will collaborate with data scientists, ML engineers, and sport scientists to deliver durable, multi‑tenant systems and robust observability across a global customer base.