Python разработчик

Fliff develops social, free-to-play sports gaming and entertainment products that allow users to compete on leaderboards and earn rewards. The company provides engaging alternatives to real-money gaming through a platform that includes sweepstakes promotions and loyalty programs.

• 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;
• Work on domain models for events, competitions, participants, markets, odds, scores, and related sports entities;
• Investigate production issues, trace data problems, and improve system observability;
• Collaborate with backend, product, trading, QA, and platform teams to deliver dependable data flows;
• Contribute to architecture decisions, code reviews, technical standards, and mentoring within the squad.

• 5+ Years of strong production experience with Python;
• Experience designing and operating backend services in production;
• Solid Django experience with asynchronous programming skills (asyncio);
• Production experience with Apache Kafka;
• 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 with monitoring, logging, alerting, and debugging production systems;
• Senior ownership mindset with the ability to break down ambiguous problems and make pragmatic technical decisions;
• Strong problem-solving skills and comfort doing code reviews;
• Willingness to participate in on-call rotations;
• Nice to have: Experience in sports betting, gaming, fantasy sports, sports data, fintech, trading, or other real-time data domains, experience with Django, Kafka, Redis, PostgreSQL, or similar technologies, experience with Go / Golang, experience with event-driven architecture or message queues, experience building data validation, reconciliation, or replay systems, cloud, Docker, Kubernetes, or infrastructure-as-code experience, interest in using AI-assisted engineering tools.

• No conditions specified