Senior QA Data Engineer

Posted 49 Minutes Ago
Easy Apply
Hiring Remotely in USA
Remote or Hybrid
130K-150K Annually
Senior level
Artificial Intelligence • Insurance • Machine Learning • Software • Analytics
Powering a Better Return on Risk
The Role
Build and maintain automated data quality testing for customer data pipelines. Responsibilities include developing dbt, Soda, and SQL checks; validating schemas, loads, sequencing, and downstream reconciliations; detecting anomalies; managing severity levels and customer overrides; reporting quality metrics; and partnering with engineering teams to embed testing into new pipelines. The role requires strong backend testing, SQL, Python, Airflow, and Databricks experience, along with excellent debugging and communication skills.
Summary Generated by Built In

**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

What the Team is Saying

Rachel
Stan
Arianna
Max
Salar
David Gal-Chis
Jake Evans
Courtney Yablecki

Gradient AI Compensation & Benefits Highlights

  • Healthcare Strength — Health coverage is described as comprehensive, including medical, dental, and vision with HSA/FSA options and mental-health/EAP, and some listings note day-one eligibility. Feedback suggests this is a standout element of the package.
  • Leave & Time Off Breadth — Time off is framed as unlimited PTO paired with 11 paid holidays and periodic companywide Recharge Days. This mix is positioned to support work-life balance.
  • Equity Value & Accessibility — Equity is offered to new hires with four-year vesting and potential additional grants via promotions/merit. This structure aims to make ownership accessible across roles.

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The Company
HQ: Boston, MA
130 Employees
Year Founded: 2018

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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Gradient AI Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Working from the office is optional if you are local to our Boston office. For employees who do come in, it’s usually T/W/Th to focus on group collaboration.

Typical time on-site: Flexible
HQBoston, MA
Our headquarters are in the Seaport area with plenty of restaurants and coffee shops close by. Plus, it's easy to get to from public transportation.

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