Senior Data Integrity Engineer

Pearl is shaping the future of dentistry with AI solutions for improved quality and care. They are seeking a Senior Data Integrity Engineer to analyze vendor data, build automated quality monitoring systems, and ensure data accuracy to enhance product recommendations.

Responsibilities:

• Analyze incoming vendor data across every domain we integrate with to identify omissions, inaccuracies, and inconsistencies — the data is complex, and the problems are often subtle
• Build automated data quality monitoring and alerting — design and implement systems that catch problems before they reach our customers
• Measure and improve the precision and recall of our recommendations — quantify the impact of data issues, prioritize by product impact, and track improvement over time
• Own vendor data quality relationships — work directly with data providers through structured reporting, regular syncs, and formal SLAs to drive upstream fixes
• Proactively detect stale or broken data connections and find ways to reduce the manual overhead required to keep them healthy
• Write application code to validate, transform, and reconcile incoming data — not just queries, but programmatic detection and correction systems
• Communicate findings to engineering, product, and leadership — translate data problems into product impact that drives prioritization

Requirements:

• Senior-level engineering skills — you're a strong programmer, not an analyst who can script. You can build production systems, not just notebooks
• Node.js proficiency — TypeScript experience is a plus. Our stack is Node, AWS Lambda, PostgreSQL, with Snowflake available for analytical workloads
• Strong SQL skills — you'll live in PG and Snowflake, exploring large datasets to find patterns in what's missing or wrong
• Product mindset — you think about data quality in terms of 'what does this do to the user's experience,' not just 'is this field populated.' You'll need to understand our product deeply to do this job well
• Self-directed problem finder — you don't wait to be told what's broken. You dig, you notice, you quantify, and you propose the fix
• Comfortable owning vendor relationships — you'll be on calls with data providers, writing up findings, pushing for fixes. This requires clarity, persistence, and professionalism
• Enthusiastic about agentic software development — you actively use tools like Cursor and Claude Code to multiply your output. This isn't optional or aspirational; it's how you work today
• Healthcare or insurance domain knowledge is a plus, not a requirement — if you've worked with complex, regulated data where accuracy has real consequences, great. If not, you need the curiosity and capacity to learn fast