Senior QA Data Engineer

We are looking for a detail-oriented and creative thinker to join our team as a Senior QA Data Engineer. In this role, you will establish the next generation of data quality and testing at Gradient AI. The successful candidate will be responsible for ensuring the quality and trustworthiness of the customer data that powers our products by designing, building, and running automated data quality checks across our data pipeline. This individual will collaborate with engineering and customer-facing teams to catch data issues before they reach production. The ideal candidate is meticulous, comfortable working in an agile environment, a team player, a strong communicator, and ready to hit the ground running at a fast-growing AI startup.

How will you make an impact:

• Build and maintain an automated data quality suite that runs on data refreshes through Airflow, replacing manual, per-customer validation.
• Define checks as code (dbt tests, Soda, custom SQL) managed through version control and CI, including baseline checks so that new pipelines get coverage by default.
• Validate loads for completeness, sequencing, and schema before processing, and halt or quarantine failures.
• Reconcile data across Databricks layers and against downstream outputs such as pricing tools, at the portfolio, group, member, and claim level, using tolerance thresholds.
• Detect anomalies, edge cases, and unexpected changes in historical data between loads.
• Define severity levels and per-customer overrides and produce a data quality report for each customer that gates promotion to downstream consumers.
• Track quality metrics over time to retire flaky checks and close coverage gaps.
• Partner with engineers so that new pipelines ship with checks built in, and give engineers, stakeholders, and project managers timely feedback on quality issues and risk.

Skills needed to succeed:

• 5+ years of professional experience in quality assurance with a strong focus on backend automated testing.
• Hands-on experience building automated data tests with Soda, dbt, or similar frameworks.
• Strong SQL skills (Spark SQL a plus) and familiarity with Python.
• Experience with Airflow or similar orchestration tools, and with Databricks or a similar lakehouse environment (Delta Lake).
• Familiarity with version control and CI/CD.
• Solid understanding of testing principles, including functional, integration, and regression testing, applied to data pipelines.
• Excellent analytical, debugging, and root-cause skills.
• Strong verbal and written communication skills, including clear defect reports and quality summaries for technical and non-technical audiences.
• Ability to work independently and coach others on testing best practices.
• Bonus: Experience with health insurance or healthcare data, anomaly detection or data observability tools, or front-end test automation tools such as Cypress or Playwright.

Tools we use:

dbt, Soda, SQL (Spark SQL), Python, Airflow, Databricks (Delta Lake)

What we offer:

• A fun, team-oriented startup culture.
• Generous stock options - we all get to own a piece of what we’re building.
• Unlimited vacation days.
• Flexible schedule that supports working from home.
• Full benefits package including medical, dental, vision, 401k, and more.
• Ample opportunities to learn and take on new responsibilities.