Data QA Engineer

Stealth-mode AI-powered Cloud-Native Health-Tech company is looking for a great, long-term Mid-level Data QA Engineer.

The focus of the role is testing ETL data loads and making sure the data in BigQuery and Spanner is complete, accurate, and consistent with business requirements.

Day to day, you will validate data loads from source to target, check transformation logic, investigate data discrepancies, and document issues so engineers can fix them quickly. Pipeline development and fixes are handled by data engineers; your role is to find problems, trace where they come from, and confirm that fixes work.

Since working with healthcare data, an important part of the job is learning the medical domain: clinical codes, terminology, and business rules that define what correct data looks like.

The company uses AI tools actively in our work and expects you to do the same, for example, to write SQL checks, prepare test cases, and analyze issues faster, while always verifying the results yourself.

This role is a good fit for someone with strong SQL skills, experience testing ETL processes, attention to detail, and an interest in learning a complex business domain.

Compensation and Benefits:

Paid Time Off

The company has Unlimited PTOs Policy and compensated New Years Holidays on top of that. The misuse of the policy isn’t welcomed, though it’s definitely possible to take at least two weeks – and fully compensated – vacation, or more.

Corporate Hardware

The company provides Corporate Hardware for employees who completed their Probationary Period, as well as proven their value.

Target Stack

NOTE: Similar cloud-native experience is always an option.

NOTE: Hands-on experience with every tool is NOT required; strong SQL and data testing skills are what matter most.

Some Bits of Our Stack

• SQL (complex queries, window functions, CTEs)

• AI tools (Claude, ChatGPT, GitHub Copilot, Cursor)

• Test management tools (Zephyr, TestRail, Jira)

• Git…