Data Engineer
Company Overview
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.
Role Overview
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.
Core Responsibilities
Trading Infrastructure Development
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
Production Systems & Operations
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
Required Qualifications
Technical Fundamentals
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
Infrastructure & Tools
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
Core Competencies
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
Strongly Preferred
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
Nice to Have
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++
Base salary: Starting at $140,000 base
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.
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