Remote Real-Time ML & Data Engineer - Sports Analytics

Andersen; United States; Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote/Hybrid work

Mentoring program

Career growth

Bonus opportunities

Training portal

Social events

Certification compensation

Referral program

Health insurance

Sports compensation

Job summary

Andersen is hiring an ML/Data Engineer to build an AI-powered sports performance platform, delivering scalable data solutions and real-time insights for coaches and athletes worldwide.

You will design production data infrastructure for high-volume sensor and time-series data, implement streaming ingestion, and build multi-tenant architectures with strong data provenance and observability. Proficiency in Python and SQL is required.

Qualifications

• Strong Python and SQL skills.
• Experience with time-series databases and real-time data ingestion.
• Experience designing graph data models and multi-tenant systems.
• Production data infrastructure experience at scale.
• Collaboration with data scientists/ML engineers.

Responsibilities

• Designing and building production data infrastructure for high-volume athlete performance and sensor data.
• Building and operating real-time and near-real-time ingestion systems for streaming data.
• Designing storage and data architectures for high-volume time-series data and longitudinal athlete records.
• Building infrastructure that makes production features and derived metrics available to ML systems with low latency.
• Designing graph data models and schemas for relationships between athletes, training loads, injuries, performance, and outcomes.
• Building data and ML evaluation infrastructure to measure model reliability and performance.
• Maintaining tenant-level data isolation across clubs and customers.
• Establishing data provenance, lineage, and observability across the platform.
• Working with ML/AI engineers to provide reliable data foundations for model training and inference.
• Translating domain requirements into durable production systems.

Skills

Python

SQL

Real-time data

Time-series data

Graph data models

Multi-tenant systems

Data infrastructure

Production systems reliability

ML data collaboration

English proficiency

Tools

InfluxDB

TimescaleDB

Prometheus

ClickHouse

Kafka

Kinesis

Flink

Spark Streaming

Pulsar

Go

AWS (ECS, EC2, Lambda, SNS, SQS)

GraphQL

REST

gRPC

Postgres

MongoDB

Job description

Andersen is hiring an ML/Data Engineer to build an AI-powered sports performance platform, delivering scalable data solutions and real-time insights for coaches and athletes worldwide.

You will design production data infrastructure for high-volume sensor and time-series data, implement streaming ingestion, and build multi-tenant architectures with strong data provenance and observability. Proficiency in Python and SQL is required.