Backend and Data Engineer, Sleeper

• 4+ years of backend and/or data-engineering experience with Python (FastAPI, Django, or similar) plus strong SQL chops
• Proven track record designing distributed systems that handle high-volume, low-latency workloads
• Experience with stream processing (Kafka, Pub/Sub, Flink or Beam) and warehouse technologies (BigQuery, Snowflake, or Redshift)
• Comfortable—or eager to learn—Elixir/Erlang and other functional stacks
• Pragmatic engineer who anticipates edge cases and failure modes in financial or real-time environments
• Calm, methodical communicator during incidents; you thrive under pressure

Desirable

• Sleeper is a rapidly growing platform for sports fans with messaging and gameplay at its core
• While much of our stack is Elixir-driven, this role bridges Python data services with our Elixir backend, GCP, and distributed analytics stores
• You’ll own the data plumbing that powers real-time pricing, risk analytics, and settlement while collaborating across product, data-science, and trading teams
• Design & implement real-time data pipelines (Python, SQLX, BigQuery) that ingest odds, bets, and exposure signals with low latency
• Build and operate backend micro-services for pricing, settlement, and limit management that expose clean gRPC/REST contracts to our Elixir cluster
• Architect a feature store that serves models in production and supports ad-hoc analytics with strong data governance
• Integrate streaming & pub/sub systems (Kafka / Google Pub/Sub) with caching layers (Redis, ScyllaDB) to guarantee consistency under high throughput
• Harden CI/CD, observability, and incident-response runbooks so data integrity issues surface before they hit users
• Partner with data scientists to deploy and monitor models end-to-end, from training to online inference
• Own projects from ideation through production, balancing delivery speed against the safety demands of real-money systems