Senior ML Data Engineer — Real-Time Sports Analytics

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

Benefits offered by this job

Health benefits

Dental benefits

Vision benefits

401(k) retirement plan with company‑m

Paid leave & holidays

Job summary

Catapult is hiring a Senior ML / Data Engineer to design and own production data infrastructure for high-volume, time-series athlete data across a global platform.

You will work with data scientists, ML engineers, and sport scientists to deliver reliable, scalable systems, with a focus on real-time ingestion, graph data models, and low-latency feature serving. This is a senior production role with ownership expectations.

Qualifications

• 5+ years of full-time professional software or data engineering experience.
• 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, etc.).
• Experience designing graph data models or graph schemas (not just querying).
• Experience designing or operating multi-tenant systems with data isolation.
• Strong Python and SQL skills; Go is highly desirable.
• Experience with reliability, observability, and data correctness in production systems.
• Experience collaborating with data scientists/ML engineers.
• Experience with causal inference, counterfactual modelling, or simulation.
• Experience with wearable sensors, IoT data, biomechanics, or sports technology.
• Experience building knowledge graphs or domain ontologies.
• Experience with AI evaluation frameworks and understanding their limitations.
• Experience with cloud services (ECS, EC2, Lambda, SNS, SQS) and related tooling.
• Experience with GraphQL, REST, gRPC, Postgres, MongoDB or similar technologies.

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.
• Provide low-latency feature serving for ML/AI systems and agents.
• Design graph data models and schemas representing relationships between athletes, training loads, injuries, and outcomes.
• Build data/ML evaluation infra to measure model reliability and calibration in real-world use.
• Ensure tenant-level data isolation across clubs and customers.
• Establish data provenance, lineage, auditability, and observability across the platform.
• Collaborate with ML/AI engineers to support model training, inference, and evaluation.
• Work with sport scientists to translate requirements into durable production systems.
• Make pragmatic technology and architecture decisions as the platform evolves.

Skills

Python

SQL

Go

Production systems

Time-series data

Graph data models

ML collaboration

Ownership of architecture

Tools

InfluxDB

TimescaleDB

Prometheus

Kafka

Kinesis

Flink

Spark Streaming

Pulsar

GraphQL

PostgreSQL

MongoDB

Neo4j

Job description

Catapult is hiring a Senior ML / Data Engineer to design and own production data infrastructure for high-volume, time-series athlete data across a global platform.

You will work with data scientists, ML engineers, and sport scientists to deliver reliable, scalable systems, with a focus on real-time ingestion, graph data models, and low-latency feature serving. This is a senior production role with ownership expectations.