Senior Real-Time ML/Data Infrastructure Engineer

Catapult Group; Northern, New York (KY, NY); Hybrid; USD 158,000 - 259,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

401(k) with company match

Job summary

Catapult is building the future of sports performance technology. We seek a Senior ML/Data Engineer to own production data infrastructure powering real-time athlete data and ML workflows for a global, multi-tenant platform.

You will collaborate with data scientists, ML engineers, software engineers, and sport scientists to design scalable systems with low latency and strong data provenance. Ownership of architecture is key.

Qualifications

• 5+ years of full-time professional software or data engineering experience.
• Proven experience designing, building, and operating production data infrastructure at scale.
• Experience with time-series data and time-series databases.
• Experience with real-time or streaming data ingestion (Kafka, Kinesis, Flink, Spark Streaming).
• Experience designing graph data models and multi-tenant systems.

Responsibilities

• Design and build production data infrastructure for high-volume athlete data.
• Build and operate real-time and near-real-time ingestion systems for streaming data.
• Design storage and data architectures for time-series data and longitudinal records.
• Provide data foundations for ML models and AI agents with low latency.
• Develop graph schemas representing relationships between athletes, training data, and outcomes.
• Establish data provenance, auditability, and observability across the platform.
• Collaborate with data scientists and ML engineers to translate requirements into durable systems.

Skills

Time-series data

Python

SQL

Kafka

Go

Data engineering

Production systems

Graph data models

Multi-tenant systems

AWS

Postgres

MongoDB

Tools

InfluxDB

TimescaleDB

Prometheus

ClickHouse

Job description

Catapult is building the future of sports performance technology. We seek a Senior ML/Data Engineer to own production data infrastructure powering real-time athlete data and ML workflows for a global, multi-tenant platform.

You will collaborate with data scientists, ML engineers, software engineers, and sport scientists to design scalable systems with low latency and strong data provenance. Ownership of architecture is key.