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Senior QA Data Engineer

Role overview

Summary

This role focuses on establishing data quality and testing at Gradient AI. You will ensure the trustworthiness of customer data by designing and running automated checks across the data pipeline, collaborating with engineering and customer-facing teams to address data issues before they reach production.

Qualifications

  • 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.
  • Solid understanding of testing principles, including functional, integration, and regression testing, applied to data pipelines.

Responsibilities

  • Build and maintain an automated data quality suite that runs on data refreshes through Airflow.
  • Define checks as code managed through version control and CI, including baseline checks for new pipelines.
  • Validate loads for completeness, sequencing, and schema before processing, and halt or quarantine failures.
  • Reconcile data across Databricks layers and against downstream outputs using tolerance thresholds.

Key facts

Hard skills

Other skills

  • Analytical Skills
  • Communication
  • Teamwork
  • Problem Solving

About the company

Gradient AI logo

Gradient AI

  • Insurance
  • 51–200
Gradient AI provides award-winning artificial intelligence (AI) solutions for the insurance industry. Its 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. Unlike other AI solutions that use a limited claims and underwriting dataset, Gradient's SaaS platform leverages a vast industry data lake comprising tens of millions of policies and claims. It also incorporates key features including economic, health, geographic, and demographic information. 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. By using Gradient AI's solutions, insurers of all types achieve a better return on risk. We are proud to have been recognized by Built In five years in a row, including two categories in 2025––Best Place to Work in Boston and Best Midsize Places to Work in Boston! Check out our page here: https://www.builtinboston.com/company/ Gradient AI was founded in to address the need for state-of-the-art AI and Machine Learning (ML) solutions for the trillion-dollar insurance industry. Our software-as-a-service platform uses AI to help commercial insurers automate and improve underwriting results, reduce claim costs, and improve operational efficiencies. Our software and models are utilized by many of the world’s most recognized Insurance Carriers, MGAs, TPAs, Pools, PEOs and more. Our team of expert Data Scientists and Insurance Technology experts have an exceptional history of building wildly successful insurance technology companies, with the most satisfied customers in the industry. At GradientAI we focus exclusively on delivering measurable results for your underwriting and claims operations.

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Job description

**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.  

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