ML/Data Engineer

About the role

Builds and runs production data infrastructure for athlete performance and sensor data, including streaming ingestion, time-series storage and graph models. The work gives machine learning systems and AI agents reliable, low-latency data foundations.

What you will do

• Design and operate production data infrastructure for large volumes of athlete performance and sensor data
• Build real-time and near-real-time ingestion pipelines for streaming data
• Architect storage for high-volume time-series data and long-term athlete records
• Create graph data models and schemas linking athletes, training loads, injuries, performance and outcomes
• Build evaluation infrastructure to measure model reliability, calibration and performance on real cases
• Ensure tenant-level data isolation, provenance, lineage, auditability and observability across the platform

What they look for

• Proven record designing, building and running production data infrastructure at scale
• Strong hands-on work with time-series data or databases such as InfluxDB, TimescaleDB, Prometheus or ClickHouse
• Significant experience with real-time or streaming ingestion using Kafka, Kinesis, Flink, Spark Streaming or Pulsar
• Strong Python and SQL skills, plus experience with multi-tenant systems and tenant-level isolation

Nice to have

• Professional Go experience
• Causal inference, counterfactual modelling or simulation
• Wearable sensors, IoT, biomechanics or sports technology data