Ensure the accuracy of data and the health, reliability, and observability of analytics and data systems.
Build monitoring, alerting, and validation frameworks for early detection of data issues, pipeline failures, performance degradation, and system-level risks.
Develop SQL-based data quality checks, Python-driven automation, and reliability safeguards to monitor data pipelines, transformations, and analytics outputs.
Track system health signals such as freshness, volume anomalies, latency, and job stability.
Define reliability standards, SLAs, and alerting strategies with data engineering, analytics, and platform teams.

Requirements

Advanced SQL skills for building data quality checks, anomaly detection, alerting logic, and monitoring queries, ideally in Snowflake or similar cloud data warehouses.
Strong Python proficiency for automation, validation frameworks, orchestration, and system health checks.
Experience designing and maintaining data quality and reliability frameworks, including freshness, completeness, accuracy, volume, and schema validation.
Solid understanding of data pipelines and analytics workflows, including ETL/ELT processes, transformations, and downstream consumption.
Experience monitoring system and pipeline health, including job failures, latency, throughput, and SLA adherence.
Familiarity with alerting and observability concepts, such as thresholds, anomaly detection, alert fatigue reduction, and incident prioritization.
Ability to perform root-cause analysis and contribute to remediation and prevention of recurring issues.
Experience with automation and testing frameworks such as Playwright, Selenium, Cypress, or similar tools is a strong asset.
Understanding of end-to-end testing concepts, including validation of analytics dashboards, alerts, and user-facing data flows.
Ability to integrate automated checks into CI/CD or scheduled workflows.
Proficiency with version control (Git) and collaborative development workflows.
Experience writing maintainable, well-documented code and SQL.
Familiarity with CI/CD pipelines, task schedulers, or orchestration tools (e.g., Airflow, dbt, or similar) is beneficial.
Strong analytical mindset with attention to detail and a proactive approach to identifying risk.
Ability to work cross-functionally with data engineering, analytics, and platform teams.
Clear communication skills to explain data and system issues to both technical and non-technical stakeholders.

Benefits

Professional Growth: Work on a variety of projects, enhancing your testing skills across different applications and technologies.
Impactful Work: Play a key role in delivering high-quality solutions that shape the future of the sports and entertainment industries.
Collaborative Environment: Be part of a team that values ideas, fosters a supportive atmosphere, and encourages continuous learning and improvement.
Innovative Culture: Join a company committed to revolutionizing fan and stakeholder engagement through cutting-edge technology.
Equal Opportunity Employer: Two Circles is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLPythondata quality checksanomaly detectionETLELTroot-cause analysisautomation frameworkstesting frameworksversion control

Soft Skills

analytical mindsetattention to detailproactive approachcross-functional collaborationclear communication