Senior QA Data Engineer

Gradient AI; Boston (MA); Remote; USD 130,000 - 150,000; Full time

Benefits offered by this job

Stock options

Flexible schedule - work from home

Full benefits package

Job summary

Gradient AI is seeking a Senior QA Data Engineer to build automated data quality checks across our data pipeline and ensure trust in customer data powering our AI products. You will validate loads, define checks as code, and collaborate with engineering to ship pipelines with built-in quality gates.

The role requires 5+ years in QA, strong SQL/Python, experience with Soda/dbt, Airflow, and Databricks. Flexible remote work in the US is offered with a comprehensive benefits package.

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 (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.

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.

Skills

QA automation

dbt tests

Soda

SQL

Python

Airflow

Databricks

Version control

CI/CD

Testing principles

communication

independent work

Cypress/Playwright (bonus)

Tools

Airflow

Databricks

Delta Lake

Job description

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.

What we offer:

• A fun, team-oriented startup culture.
• Generous stock options - we all get to own a piece of what we're building.
• 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: $1 30 ,000- 1 50 ,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.

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey.Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in aconfidential file.

As set forth in Gradient AI’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows:

A \"disabled veteran\" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service‑connected disability.

A \"recently separated veteran\" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An \"active duty wartime or campaign badge veteran\" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An \"Armed forces service medal veteran\" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.