Senior Data QA Engineer

Abacus Insights is transforming healthcare data usability for health plans. As a Senior Data QA Engineer, you will ensure the accuracy and compliance of healthcare data while leading the development of automated testing frameworks and mentoring junior engineers.

Responsibilities:

• Architect, build, and maintain enterprise-scale automated data quality validation frameworks, including rules engines, anomaly detection, and monitoring for completeness, conformity, integrity, and timeliness
• Lead design and implementation of automated test strategies for complex healthcare data ingestion, transformation, and downstream application pipelines
• Drive root cause analysis on high-impact data quality defects, own remediation strategy, and prevent recurrence through systemic process improvements
• Define and evolve data quality strategy, standards, and best practices across pipelines, influencing tooling and process decisions org-wide
• Partner directly with Engineering, Product, Project Management, Operations, and Connector Engineering leadership to translate business and compliance requirements into technical test plans, functional specifications, and validation logic
• Lead review of software and data defect reports, identify systemic problem areas, and establish standards for reproducible issue documentation
• Design and maintain advanced QA automation frameworks and dashboards using SQL, Python, Java, and cloud-native tooling
• Lead system verification protocol design and represent QA in cross-functional architecture and design discussions
• Conduct advanced data mining and profiling on client-specific and healthcare datasets to proactively surface quality risks at scale
• Own documentation strategy including test plans, validation criteria, rule catalogs, and QA runbooks
• Mentor and provide technical guidance to junior and mid-level QA engineers
• Serve as an escalation point for internal and external data quality inquiries
• Ensure data security and quality processes align with PHI handling, HIPAA, SOC 2, and Abacus governance requirements, and help evolve governance standards as the platform scales

Requirements:

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Analytics, or related technical field, or equivalent work experience
• 6–8+ years of experience in Data Quality Engineering and Data Engineering, with significant experience in healthcare technology or payer/provider environments
• Expert-level SQL skills, including complex data manipulation, validation, and profiling at scale
• Proven ability to lead data quality projects end-to-end
• Deep experience working with healthcare data types such as enrollment, medical claims, pharmacy claims, provider data, or non-traditional health and wellness datasets
• Strong hands-on automation scripting expertise in Python or Java, with a track record of building reusable frameworks
• Proven experience with cloud computing environments such as AWS (S3, EC2, SSM, Athena) and Databricks in production-scale settings
• Demonstrated experience designing data integration workflows, ETL/ELT pipelines, data mapping strategy, and enterprise QA testing protocols
• Track record of building and scaling automated QA applications, dashboards, or custom rule frameworks from the ground up
• Proven ability to analyze complex, large-scale datasets, identify systemic quality issues, and drive actionable, measurable improvements
• Experience mentoring engineers and influencing technical direction across teams
• Excellent communication skills, with the ability to work cross-functionally, influence stakeholders, and operate independently with minimal oversight
• Strong organizational and prioritization skills in a fast-paced, multi-project environment
• Deep exposure to Delta Lake, Spark, Airflow, dbt, or event-driven architectures
• Advanced knowledge of schema evolution management (Parquet, Avro, ORC, JSON)
• Experience leading data quality lifecycle management initiatives in large-scale cloud systems
• Familiarity with Terraform, DevOps pipelines, CI/CD workflows, Git-based version control
• Background in software debugging, system testing methodologies, or performance testing at an architectural level