Data Engineer
About The Position
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients. You'll be building trading infrastructure for sports betting platforms, leveraging our proprietary fair value models to gain trading edge. This is a high-impact role where you'll architect and deploy low-latency systems that make real-time trading decisions.
Requirements
- 3+ years of production Python experience with strong async programming skills
- Deep understanding of Python's async/await patterns, event loops, and concurrent execution
- Experience building and maintaining production services in Linux environments
- Strong system design skills for distributed, real-time data processing systems
- Proficiency with SQL databases and data modeling
- Experience with containerization (Docker) and orchestration (Kubernetes)
- Familiarity with message streaming platforms (Kafka preferred)
- Understanding of monitoring, logging, and observability practices
- Git workflows and CI/CD pipelines
- Ability to write clean, maintainable, well-tested code
- Strong debugging skills and systematic problem-solving approach
- Comfortable working in a fast-paced environment with evolving requirements
- Self-directed with ability to make pragmatic technical decisions
Nice To Haves
- Experience with trading systems, market-making, or order book dynamics
- Knowledge of sports betting markets or financial trading ecosystems (TradFi/Crypto)
- Experience with Protobufs, Argo Workflows, or similar tools in our stack
- Background in high/mid-frequency or low-latency system design
- Understanding of WebSocket protocols and real-time data streaming
- Exposure to FIX protocol or other financial messaging standards
- Experience with Streamlit or similar tools for rapid dashboard development
- Knowledge of database CDC patterns (Debezium, etc.)
- Contributions to open-source trading or data infrastructure projects
- Experience working with Rust or C++
Responsibilities
- Build and optimize market-making engines that consume real-time order book data and execute trades across multiple platforms
- Develop low-latency data ingestion pipelines for market data feeds (WebSocket, FIX protocol, REST APIs)
- Create real-time edge analysis systems that compare our fair values against live market prices to identify profitable opportunities
- Implement order management systems with robust error handling, position tracking, and risk controls
- Deploy and manage containerized applications on Kubernetes
- Build automated testing, deployment, and rollback procedures for trading systems
- Design and implement post-trade analysis tools to evaluate strategy performance
- Handle production incidents and optimize system performance under load
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
1-10 employees
