Data Engineer at Motive delivering data infrastructure for the AI era. Collaborating with stakeholders, building models, and implementing innovative tooling.
About the role
- Data Engineer In Test ensuring data reliability and observability for sports marketing analytics. Collaborating with cross-functional teams to build monitoring frameworks and validation checks.
Responsibilities
- 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.
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