Data QA Engineer

About the role

Abacus Insights is transforming how data works for health plans. Our mission is simple: make healthcare data usable, so the people responsible for care and cost decisions can act faster, with confidence. We help health plans break down data silos to create a single, trusted data foundation. That foundation powers better decisions-so plans can improve outcomes, reduce waste, and deliver better experiences for members and providers alike. Backed by $100M from top investors, we're tackling big challenges in an industry that's ready for change. Our platform enables GenAI use cases by delivering clean, connected, and reliable healthcare data to support automation, prioritization, and decision workflows-and it's why we are leading the way. Our innovation begins with people. We are bold, curious, and collaborative-because the best ideas come from working together. We embrace the thoughtful use of AI and automation to drive innovation and efficiency, and we look for individuals who are curious and adaptable-those excited to leverage emerging technologies to enhance how we work-while keeping human insight, connection, and our clients at the center of every decision. Ready to make an impact? Join us and let's build the future together. Our TechOps team is looking to bring on an experienced Data QA Engineer. If you are interested in being a guiding voice on a critical feature delivery team, this position is for you. The team is responsible for implementing and configuring the data pipelines that ingest and do the ETL and process diverse sources of data. This includes building large batch processing and streaming systems. You will be exposed to every area of our platform and AWS services (Serverless - Lambda, EMR - Hadoop/Spark, EKS - Kubernetes, etc.) but even more so, help drive the evolution of the product and team as we continue to grow rapidly. We believe heavily in architecture evolution, and you will bring your experience to best practices as we build out new components of the platform. Your day to day: Review mapping specifications to identify business requirement gaps and estimated QA efforts. Design ETL test scenarios and test cases, validated input file layouts and parsers. Write source-to-target SQL queries for data validation and user acceptance criteria Automate data validation using PySpark and Databricks Execute testing using synthetic data resembling real‑time production scenarios Support UAT, worked in Agile methodology, tracked QA activities in Jira/test management tools, and coordinated onsite-offshore teams

Requirements

• Bachelor's degree in computer science, Engineering, Information Technology, or related field, with 2+ years of hands‑on experience in Data QA or Data Engineering QA
• Strong expertise in SQL, including complex queries, joins, aggregations, performance optimization, and data validation
• Working knowledge of Python for data analysis, synthetic data creation, and automation of QA processes
• Proven ability to analyze large datasets, identify inconsistencies, and validate business logic
• Solid understanding of QA methodologies with experience designing test cases for data‑centric systems
• Experience with PySpark, Databricks, and AWS services such as Redshift, S3, and Athena; familiarity with analytics and reporting tools is a plus
• Experience with BigQuery, Snowflake, and ETL test automation
• Hands‑on API testing experience
• Healthcare domain knowledge, including HEDIS quality measures
• What you'll get in return
• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee - share in our success
• Growth-focused environment - your development matters here
• Working Arrangements
• Standard hours: 9 hours/day, 5 working days
• Location: Onsite
• Shift: 10 AM - 7 PM local time
• Our Commitment as an Equal Opportunity Employer

Benefits

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at abacusinsights? Share your experience