Senior Python/SQL Developer

Fliff unpacks sports gaming into social, free-to-play games for all types of sports fans. We've built a social sports gaming experience that allows users to compete for leaderboard positioning, to achieve badges and build their status within the game.
We are pioneering play-for-fun sports gaming, with our flagship social sportsbook experience that includes sweepstakes promotions and loyalty rewards. Behind every market, event, contest, player prop, and in-app experience is a data platform that needs to be accurate, reliable, and fast.
The DataFeed Team owns the systems that bring external sports data into Fliff: ingesting feeds, normalizing provider-specific formats, validating data quality, and making that data available to the rest of the platform.
We are looking for a Senior Python Engineer to help us build and evolve the core systems behind Fliff’s sports data platform.
You will help make sure our data is correct, timely, observable, and resilient when external feeds behave unpredictably.
The systems you build will support real-time experiences across Fliff and help our teams move faster with confidence.
Design, build, and maintain Python services for sports data ingestion, transformation, and distribution
Integrate with third-party sports data providers and handle differences between provider models, formats, and update patterns
Build reliable pipelines for near real-time and batch data processing
Improve data validation, reconciliation, monitoring, alerting, and replay tooling
Investigate production issues, trace data problems, and improve system observability
Collaborate with backend, product, trading, QA, and platform teams to deliver dependable data flows
5+ years of strong production experience with Python

• Solid understanding of APIs, distributed systems, async processing, and data pipelines
• Strong SQL skills and experience with relational databases, especially PostgreSQL
• Experience integrating with external APIs, feeds, or third-party data providers
• Ability to reason carefully about data correctness, edge cases, and failure modes
• Experience in sports betting, gaming, fantasy sports, sports data, fintech, trading, or other real-time data domains

Experience with Go / Golang , especially for high-throughput backend services, data processing, or performance-sensitive systems
Experience building data validation, reconciliation, or replay systems
Sports data is full of real-world complexity. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.