Quality Assurance Engineer

About the role

We're looking for a QA Engineer who approaches quality as an engineering problem. This is NOT just a manual testing role — it's for an engineer who writes automation to proactively find bugs, surface data quality issues at scale, and then writes or contributes code to fix them.

The ideal candidate is a strong programmer who is comfortable working across large datasets, debugging complex pipelines, and owning quality end-to-end: from detection to fix.

We want someone who thinks like a software engineer first and a quality advocate second: someone who sees a data anomaly or product bug and immediately thinks "how do I build something that catches this automatically — and then fixes it?" You should be energized by ambiguity, comfortable digging into large datasets and production logs, and able to move quickly without waiting to be handed a spec.

What You'll Do

• Design and build automated systems that identify data quality issues, product bugs, and regressions across our web application and data pipelines — reducing reliance on manual discovery.
• Write scripts and tooling to detect anomalies, inconsistencies, or failures in large datasets (e.g. malformed records, missing relationships, unexpected distributions).
• Work with product to prioritize identified issues based on business impact, and write or contribute code fixes directly — not just file tickets.
• Develop and maintain automated test coverage (unit, integration, end-to-end) with a focus on high-risk areas and data-heavy workflows.
• Collaborate with engineering to review data models, API contracts, and backend logic for correctness and edge cases.
• Instrument quality metrics and build internal tooling or dashboards to track data health and product reliability over time.
• Contribute to release readiness by running automated checks and surfacing risk areas with supporting data.

Who You Are

• 3+ years of engineering experience with a focus on quality, data integrity, or test automation.
• Strong Python skills — comfortable writing production-quality scripts, automation, and data analysis code.
• Experience working with large datasets: querying, profiling, validating, and debugging data in SQL and NoSQL databases (Postgres/Elasticsearch preferred).
• Proven track record building automated systems that discover bugs or data issues, not just validate known behavior.
• Ability to read, understand, and contribute fixes to a production codebase — this role writes code, not just tests.
• Comfortable working independently and prioritizing a backlog of quality issues by impact.

Nice to haves

• Experience with Django, Elasticsearch, or Vue.
• Familiarity with AWS-based environments and cloud data pipelines.
• Experience building data quality monitoring, alerting, or observability tooling.
• Familiarity with tools such as Pytest, Great Expectations, dbt tests, Playwright, Postman, or similar.
• Experience as the first or only QA/quality engineer on a team, including setting up processes from scratch.
• Experience working with remote or internationally distributed teams.

Benefits

• Meaningful equity
• Full Medical, dental, and vision coverage (for you and your family). ALL premiums covered!
• 401k w/ full match up to state limit
• Work from anywhere
• Flexible vacation policy. You manage your own time