Описание

This is a fully remote position. Gradient AI is a leading provider of AI solutions for the Group Health and P&C insurance industries, improving loss ratios and profitability by predicting underwriting and claim risks with greater accuracy.

Responsibilities

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

Requirements

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

Nice to have

Experience with health insurance or healthcare data
Experience with anomaly detection or data observability tools
Experience with front-end test automation tools such as Cypress or Playwright

We offer

A fun, team-oriented startup culture
Generous stock options
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
Base salary annually: 130,000-150,000 USD
This role is also eligible for an annual performance bonus, equity grant, and a comprehensive benefits package

Tools we use

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