Automated QA Engineer

At Stats Perform, we process thousands of live sports events daily—delivering real-time data to broadcasters, sportsbooks, and fans within milliseconds. As a Senior QA Automation Engineer, your focus will be building and maintaining modern automated testing systems that ensure the integrity and speed of these pipelines. There's no manual testing or outdated scripts—just clean Python, robust CI/CD, and opportunities to explore AI-powered quality tools.

We're looking for a QA Engineer (mid-level — 3+ years) who codes automation in Python and loves experimenting with AI/ML. You'll own green-field POCs, extend our web/API/data-validation frameworks, and keep traditional QA discipline—requirements analysis, structured testing, and clean defect management—at the core.
 

What you'll work on

• Design, build, and maintain automated test frameworks using Python for APIs, streaming feeds, and real-time data pipelines
• Extend and optimize our pytest-based libraries for better scalability and reusability
• Create sub-second data validators that detect integrity issues across high-volume pipelines
• Investigate latency anomalies and partner with engineers to implement performance improvements
• Prototype AI-driven QA tools like self-healing tests or anomaly detection powered by ML models
• Productionize successful prototypes into robust, scalable QA solutions
• Define and track quality KPIs—coverage, failure rates, time-to-detect—and present them through GitHub-integrated dashboards
• Automate quality gates in the CI/CD pipeline to prevent regressions before deployment
• Participate in code reviews, design sessions, and collaborative debugging with cross-functional teams
• Spend three dedicated on-site days per week in our Prague office to align with Product, DevOps, and Data Engineering

What makes you a great fit

• 5+ years of hands-on experience with Python automation (pytest, Playwright, Selenium, or similar)
• Proven track record of building end-to-end test frameworks from scratch
• Background in validating complex systems involving real-time data, APIs, or streaming technologies
• Understanding of ML concepts (e.g., scikit-learn, TensorFlow, PyTorch) and interest in AI-powered QA
• Comfortable writing SQL queries and working with structured data
• Familiarity with REST APIs, Git workflows, Docker containers, and CI/CD tools like GitHub Actions or Jenkins
• Enjoy clean code practices, code reviews, and sharing knowledge with junior testers
• Strong debugging and problem-solving mindset—you chase down edge cases others miss
• Clear communicator in English; able to document, explain, and advocate for quality initiatives

Why you'll enjoy working here

• Your work directly impacts the quality of real-time data used by millions across betting platforms and broadcasts
• Hybrid setup that balances focused remote work with face-to-face team collaboration (Tue–Thu in-office)
• Personal learning budget for Udemy, O'Reilly, certifications, and QA guild membership
• Collaborative, international team where engineers, analysts, and product managers work closely
• Premium private healthcare fully covered, plus mental health days and additional paid vacation
• "No-Meeting Fridays" for deep work and uninterrupted focus
• Two fully paid volunteer days per year—give back to causes you care about
• Inclusive culture where diverse perspectives are valued and career growth is supported

Diversity, Equity, and Inclusion at Stats Perform
At Stats Perform, diversity drives innovation. We are committed to building an inclusive, welcoming workplace where everyone is valued and respected. Our DEI goals are at the heart of our culture, ensuring we better serve our clients and communities.