About the job
About Abacus Insights
Abacus Insights helps health plans unlock the full potential of their data. The company’s mission is to make healthcare data actionable, so decision-makers can move quickly and confidently. By breaking down data silos, Abacus creates a unified, reliable foundation that supports better decisions, reduces inefficiencies, and improves experiences for both members and providers.
With $100 million in investment from top backers, Abacus is tackling some of healthcare’s biggest data challenges. Its platform supports GenAI applications by delivering clean, connected, and trustworthy healthcare data, which fuels automation and smarter workflows. Collaboration, curiosity, and bold thinking drive innovation here, Abacus believes teamwork sparks the best ideas.
Role Overview: Data Quality Engineer (Pune, India)
The Data Quality Engineer ensures the accuracy, reliability, and compliance of healthcare data within Abacus Insights’ cloud-native data management platform. This role calls for experience in data engineering, data quality frameworks, and healthcare data domains. The engineer will design automated testing, develop data validation solutions, and work closely with engineering and product teams to maintain high-quality, trustworthy datasets for health plan clients. The work directly supports both regulatory and operational standards across the company’s data ecosystem.
What You Will Do
- Design, build, and maintain automated data quality validation frameworks, including rules engines and anomaly detection, to monitor completeness, conformity, integrity, and timeliness.
- Create and maintain automated test procedures for healthcare data ingestion, transformation, and downstream applications.
- Investigate data quality defects, analyze root causes, and recommend remediation steps.
- Review and refine data quality strategies, contributing to standardized processes across data pipelines.
- Work with Engineering, Project Management, Operations, and Connector Engineering teams to align and strengthen data quality initiatives.

