Sports Operations Engineer

Summary

Kalshi is a company that has defined a new category of prediction markets, allowing people to trade on the outcome of events. The Sports Operations Engineer will be responsible for building and maintaining the automation systems that power sports markets, requiring a blend of sports knowledge and engineering skills.

Responsibilities

• Design and build Python automation scripts that list, update, and determine sports markets at scale
• Create intelligent systems that handle pre-game, in-play, and futures markets across NFL, NBA, MLB, NHL, MLS, NCAA, and international competitions without manual intervention
• Build robust data pipelines that ingest, process, and structure large volumes of sports data from multiple feeds
• Design systems that handle real-time game data, player statistics, injury reports, weather updates, and official league sources while maintaining data integrity and low latency
• Implement and maintain complex DAGs for orchestrating market operations workflows
• Design fault-tolerant systems that handle dependencies between data ingestion, market creation, live updates, and settlement processes across thousands of concurrent sporting events
• Develop and maintain cron jobs and scheduled tasks that automatically list markets at optimal times, update odds based on market conditions, and settle markets immediately after game completion
• Ensure reliable execution during high-volume periods like NFL Sundays
• Own and evolve internal tools used by the Market Operations team
• Build intuitive interfaces for market management, settlement verification, and operational monitoring
• Gather requirements from operators and continuously improve tooling to increase efficiency and reduce errors
• Translate complex sports rules and edge cases into code
• Build systems that understand overtime rules, tiebreakers, playoff scenarios, and sport-specific nuances
• Implement logic for handling postponements, suspensions, protests, and stat corrections across different leagues
• Create systems that process live game feeds and trigger appropriate market actions in real-time
• Build monitoring and alerting systems that detect anomalies, data discrepancies, or unusual game situations requiring intervention
• Develop automated settlement systems that accurately determine market outcomes based on official results
• Implement verification layers that cross-reference multiple data sources and flag potential discrepancies for review
• Continuously improve system performance to handle increasing market volumes
• Optimize database queries, implement caching strategies, and ensure our infrastructure scales smoothly during peak trading periods
• Collaborate with Product, Contracts, and broader Engineering teams to integrate sports operations systems with Kalshi's core platform
• Design APIs and services that enable seamless market operations

Skills

• Bachelor's degree in Computer Science, Data Science, or related technical field
• 1-3 years of experience as a software engineer with a proven track record of building production systems
• Strong proficiency in Python and JavaScript with experience building automation scripts, data processing systems, and web applications
• Experience with DAG frameworks (Airflow, Prefect, Dagster) for orchestrating complex workflows and data pipelines
• Expertise with cron jobs and scheduled task management in production environments, including monitoring and error handling
• Experience pulling, processing, and structuring large datasets from APIs, webhooks, and real-time data feeds. Familiarity with data formats common in sports data (JSON, XML, WebSocket streams)
• Proven ability to build automation and data pipelines that handle high-volume, time-sensitive operations with strong error handling and recovery mechanisms
• Track record of making continuous tooling improvements and building internal products that scale with team needs
• Product ownership mentality with experience gathering requirements, prioritizing features, and delivering tools that solve real operational problems
• Strong knowledge of sports and sports trading operations including understanding of different market types, settlement rules, and common edge cases across major sports leagues
• Database expertise with both SQL and NoSQL systems for storing and querying sports data efficiently
• Experience with real-time systems including WebSockets, event streaming, and message queues
• Strong debugging and troubleshooting skills with ability to quickly diagnose and fix issues in production systems
• Excellent communication skills to work effectively with non-technical operations team members and translate requirements into technical solutions
• Ability to work flexible hours including on-call rotations to support live sporting events across different time zones
• Passion for sports combined with technical excellence and a commitment to building world-class market infrastructure
• Experience with sports data providers

Qualifications

Must Haves

• Bachelor's degree in Computer Science, Data Science, or related technical field
• 1-3 years of experience as a software engineer with a proven track record of building production systems
• Strong proficiency in Python and JavaScript with experience building automation scripts, data processing systems, and web applications
• Experience with DAG frameworks (Airflow, Prefect, Dagster) for orchestrating complex workflows and data pipelines
• Expertise with cron jobs and scheduled task management in production environments, including monitoring and error handling
• Experience pulling, processing, and structuring large datasets from APIs, webhooks, and real-time data feeds. Familiarity with data formats common in sports data (JSON, XML, WebSocket streams)
• Proven ability to build automation and data pipelines that handle high-volume, time-sensitive operations with strong error handling and recovery mechanisms
• Track record of making continuous tooling improvements and building internal products that scale with team needs
• Product ownership mentality with experience gathering requirements, prioritizing features, and delivering tools that solve real operational problems
• Strong knowledge of sports and sports trading operations including understanding of different market types, settlement rules, and common edge cases across major sports leagues
• Database expertise with both SQL and NoSQL systems for storing and querying sports data efficiently
• Experience with real-time systems including WebSockets, event streaming, and message queues
• Strong debugging and troubleshooting skills with ability to quickly diagnose and fix issues in production systems
• Excellent communication skills to work effectively with non-technical operations team members and translate requirements into technical solutions
• Ability to work flexible hours including on-call rotations to support live sporting events across different time zones
• Passion for sports combined with technical excellence and a commitment to building world-class market infrastructure

Nice to Haves

• Experience with sports data providers

Benefits

• Equity and benefits