Sleeper is a rapidly growing platform for sports fans with messaging and gameplay at its core.
This role bridges Python data services with the Elixir backend, GCP, and distributed analytics stores.
You will own the data plumbing that powers real-time pricing, risk analytics, and settlement while collaborating across product, data-science, and trading teams.
Responsibilities include designing and implementing real-time data pipelines using Python, SQLX, and BigQuery that ingest odds, bets, and exposure signals with low latency.
You will build and operate backend micro-services for pricing, settlement, and limit management that expose clean gRPC/REST contracts to the Elixir cluster.
The role involves architecting a feature store that serves models in production and supports ad-hoc analytics with strong data governance.
You will integrate streaming and pub/sub systems (Kafka / Google Pub/Sub) with caching layers (Redis, ScyllaDB) to guarantee consistency under high throughput.
Responsibilities also include hardening CI/CD, observability, and incident-response runbooks to ensure data integrity issues surface before they impact users.
You will partner with data scientists to deploy and monitor models end-to-end, from training to online inference.
The position requires owning projects from ideation through production, balancing delivery speed against the safety demands of real-money systems.
Requirements:
Candidates must have 4+ years of backend and/or data-engineering experience with Python (FastAPI, Django, or similar) and strong SQL skills.
A proven track record in designing distributed systems that handle high-volume, low-latency workloads is required.
Experience with stream processing (Kafka, Pub/Sub, Flink or Beam) and warehouse technologies (BigQuery, Snowflake, or Redshift) is necessary.
Candidates should be comfortable—or eager to learn—Elixir/Erlang and other functional stacks.
A pragmatic engineering approach that anticipates edge cases and failure modes in financial or real-time environments is essential.
Candidates must be calm and methodical communicators during incidents and thrive under pressure.
Preferred skills include prior work with ScyllaDB/Cassandra, ClickHouse, or other wide-column/OLAP stores.
Hands-on experience with Kubernetes, Terraform, GitLab CI, and observability stacks (Prometheus, Grafana, OpenTelemetry) is a plus.
Familiarity with Rust, Go, or C++ for ultra-low-latency components is desirable.
Knowledge of risk modeling, market-making algorithms, or sports-betting infrastructure is also preferred.
Benefits:
The position offers a competitive salary and stock options.
Comprehensive health, dental, and vision insurance is provided.
A 401(k) plan is available for employees.
The company promotes flexible working hours and a remote-first culture.
There are clear paths for career growth and leadership opportunities within the organization.
