**This is a fully remote position.
Gradient AI:
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.
About the role:
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.
We are an equal opportunity employer.
Salary Range: $130,000-150,000 base salary annually.
This role is also eligible for an annual performance bonus, equity grant, and a comprehensive benefits package. In accordance with the Massachusetts Pay Transparency Law, we are providing a good-faith salary range for this position at the time of posting. The actual salary offered will depend on the level at which the candidate is hired, as well as their experience, skills, qualifications, and location. Compensation may grow over time through merit-based increases, promotions, and company-wide adjustments. If your salary expectations fall outside this range, we still encourage you to apply so we can have a conversation.
Skills Required
- 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 experience is a plus
- Familiarity with Python
- Experience with Airflow or similar orchestration tools
- Experience with Databricks or a similar lakehouse environment, such as Delta Lake
- Familiarity with version control and CI/CD
- Understanding of functional, integration, and regression testing principles applied to data pipelines
- Strong analytical, debugging, and root-cause analysis skills
- Strong verbal and written communication skills, including defect reports and quality summaries
- Ability to work independently and coach others on testing best practices
- 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
Gradient AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Gradient AI and has not been reviewed or approved by Gradient AI.
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Healthcare Strength — Medical, dental, and vision coverage are complemented by mental health resources, HSAs/FSAs, and an employee assistance program. Company materials also highlight disability and life insurance as part of a comprehensive package.
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Leave & Time Off Breadth — Unlimited PTO, 11 paid holidays, paid sick time, and company-wide Recharge Days are described alongside flexible and remote work options. Feedback suggests these features support work-life balance when teams can use them.
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Parental & Family Support — Twelve weeks of fully paid parental leave after one year of employment are listed. This sits alongside flexibility for remote or hybrid work, which can ease family logistics.
Gradient AI Insights
What We Do
Gradient AI is revolutionizing Group Health and P&C insurance with AI-powered solutions that help insurers predict risk more accurately, improve profitability, and automate underwriting and claims. Our SaaS platform taps into one of the industry’s largest data lakes—tens of millions of policies and claims—to deliver deep, actionable insights. Trusted by leading carriers, MGAs, TPAs, and self-insured employers, Gradient AI has grown rapidly since our founding in 2018. Backed by $56M in Series C funding, we're scaling fast—and it's an exciting time to join the team.
Why Work With Us
Gradient is a fast-growing startup where you can make an impact, learn constantly, and grow quickly. We’re bringing AI and machine learning into the insurance space in new ways, and every team member plays a role in that innovation.
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