Senior QA Data Engineer

Responsibilities

• Build and maintain an automated data quality suite running on data refreshes through Airflow
• Define data quality checks as code (dbt tests, Soda, custom SQL) under version control and CI
• Validate loads for completeness, sequencing and schema, halting or quarantining failures
• Reconcile data across Databricks layers and downstream outputs using tolerance thresholds
• Detect anomalies and unexpected changes in historical data between loads
• Produce per-customer data quality reports that gate promotion to downstream consumers
• Partner with engineers so new pipelines ship with checks built in

Requirements

• 5+ years of professional quality assurance experience with a focus on backend automated testing
• Hands-on experience building automated data tests with Soda, dbt or similar
• Strong SQL skills and familiarity with Python
• Experience with Airflow or similar orchestration tools and Databricks or a lakehouse environment
• Familiarity with version control and CI/CD
• Solid understanding of functional, integration and regression testing for data pipelines
• Strong analytical, debugging and communication skills

Preferred Qualifications

• Experience with health insurance or healthcare data
• Experience with anomaly detection or data observability tools
• Front-end test automation experience with Cypress or Playwright

Benefits

• Stock options, unlimited vacation, flexible remote schedule
• Medical, dental, vision and 401k benefits
• Annual performance bonus and equity grant

About the Company

• Gradient AI provides AI solutions for Group Health and P&C insurers, improving loss ratios and claim outcomes.
• Founded in 2018, the company raised $56 million in Series C funding.