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## About the role
We are hiring a Senior Backend Engineer to build and scale the systems powering our apps and experiences. You will work with serverless microservices and event-driven data pipelines to process millions of realtime sports odds and stats updates. This role is ideal for an engineer who enjoys ownership across API design, distributed systems, data architecture, and cloud infrastructure, and who can ship reliably in a fast-moving product environment.
## Key Responsibilities
- Design, build, and maintain serverless data pipelines that ingest, normalize, and aggregate sports data (stats, odds, play-by-play, injuries, rosters, etc.) from dozens of third-party providers.
- Own and evolve APIs and event-driven workflows, ensuring reliability, performance, and clear service boundaries.
- Build and optimize real-time processing systems to power low-latency experiences without inflating costs.
- Design efficient data models and optimize data access patterns across databases, caching, and streaming systems.
- Implement sports analytics logic (expected value calculations, team/player ranking, etc.)
- Partner with the product team to translate requirements into scalable backend architecture.
- Leverage AI-powered tools and automation to improve developer productivity, system capabilities, and overall engineering efficiency.
- Improve service reliability, observability, and operational excellence through strong logging, tracing, monitoring, and alerting practices.
## Desired Experience and Attributes
### Must-have qualifications
- 3+ years of backend engineering experience in production systems.
- Strong Python proficiency and experience building APIs and asynchronous/event-driven systems.
- Hands-on AWS experience (Lambda, API Gateway, DynamoDB; bonus for Kinesis/EventBridge/SQS/SNS/Step Functions).
- Practical testing skills and debugging in distributed systems.
- Strong communication and ownership mindset.
- Keen sense of how to use AI tooling effectively.
### Nice-to-have qualifications
- Experience working in microservice-oriented codebases with CI/CD and Infrastructure-as-Code.
- Experience building ETL pipelines using Pandas.
- Experience with Serverless Framework in multi-service repos.
- Background in sports, gaming, fintech, or other real-time/high-throughput domains.
- Exposure to Elasticsearch, Redis, PostgreSQL, and BigQuery.
## What You'll Get
- The chance to work with a powerful, comprehensive dataset for sports analytics, transforming it into user-facing experiences that engage fans and inform betting strategies.
- Meaningful ownership of complex real-time systems in a fast-growing consumer product environment.
- Direct collaboration with product and company leadership on high-impact feature
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