<p><em><strong><span data-contrast="auto">**This is a fully remote position. </span></strong></em></p> <p><strong><span data-contrast="auto">Gradient AI:</span></strong><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></p> <p><span data-contrast="auto">Gradient AI is a leading provider of AI solutions for the Group Health and P&C insurance industries. Our solutions improve loss ratios and profitability by predicting underwriting and claim risks with greater accuracy, as well as reducing quote turnaround times and claim expenses through intelligent automation. Gradient AI's SaaS platform leverages a vast industry data lake comprising tens of millions of policies and claims, providing insurers with high resolution, data-driven insights. Customers include some of the most recognized insurance carriers, MGAs, MGUs, TPAs, risk pools, PEOs, and large self-insured employers across all major lines of insurance. Founded in 2018, Gradient has experienced strong growth every year, and recently raised $56 million in Series C funding from top Insurtech investors.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></p> <p><strong><span data-contrast="auto">About the role:</span></strong><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></p> <p><span data-contrast="auto">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.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></p> <p><strong><span data-contrast="auto">How will you make an impact:</span></strong><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></p> <ul> <li><span data-contrast="auto">Build and maintain an automated data quality suite that runs on data refreshes through Airflow, replacing manual, per-customer validation.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></li> <li><span data-contrast="auto">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.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></li> <li><span data-contrast="auto">Validate loads for completeness, sequencing, and schema before processing, and halt or quarantine failures.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></li> <li><span data-contrast="auto">Reconcile data across Databricks layers and against downstream outputs such as pricing tools, at the portfolio, group, member, and claim level, using tolerance thresholds.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></li> <li><span data-contrast="auto">Detect anomalies, edge cases, and unexpected changes in historical data between loads.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></li> <li><span data-contrast="auto">Define severity levels and per-customer overrides and produce a data quality report for each customer that gates promotion to downstream consumers.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></li> <li><span data-contrast="auto">Track quality metrics over time to retire flaky checks and close coverage gaps.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></li> <li><span data-contrast="auto">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.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></li> </ul> <p><strong><span data-contrast="auto">Skills needed to succeed:</span></strong><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></p> <ul> <li><span data-contrast="auto">5+ years of professional experience in quality assurance with a strong focus on backend automated testing.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></li> <li><span data-contrast="auto">Hands-on experience building automated data tests with Soda, dbt, or similar frameworks.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></li> <li><span data-contrast="auto">Strong SQL skills (Spark SQL a plus) and familiarity with Python.</span><span data-ccp-props="{"134233117":true,"134233118":true}"> </span></li> <li><span data-contrast="auto">Experience with Airflow or similar orchestration tools, and with Databricks or a similar lakehouse environment (Delt