Associate QA Lead

Essential Duties & Responsibilities:

• Serve as an QA SME for Epic and Oracle Health (Cerner) systems, including clinical workflows, data structures, and relationships across major healthcare domains.
• Lead end-to-end data validation across healthcare applications, databases, interfaces, APIs, and integrated systems.
• Perform source-to-target reconciliation and validate record counts, field mappings, transformations, business rules, referential integrity, duplicates, missing/null values, data formats, and cross-system relationships.
• Develop and execute advanced SQL queries, including complex joins, aggregations, comparisons, and reconciliation queries, to validate large healthcare datasets and identify discrepancies.
• Validate healthcare data involving patients, providers, encounters, clinical documentation, orders/results, laboratory, medications, financial, and operational data.
• Apply deep knowledge of Epic and/or Oracle Health (Cerner) data structures, workflows, and healthcare domains to define validation strategies and troubleshoot complex data issues.
• Validate healthcare systems including EHR/EMR, LIS, Blood Bank, Financial/Revenue Cycle, ERP, HR, and other enterprise healthcare applications.
• Perform integration and interoperability testing involving HL7, CCD/C-CDA, FHIR, XML, JSON, and APIs.
• Trace data across source systems, ETL/transformation layers, databases, interfaces, and applications to identify root causes of complex data discrepancies.
• Define testing scope, data-validation strategy, acceptance criteria, and project-specific QA checklists based on requirements and risk.
• Identify and manage defects using JIRA or similar tools, perform root cause analysis, and collaborate with Development and Data Engineering teams through resolution and regression testing.
• Lead multiple QA projects, proactively identify quality risks, and communicate testing status and issues to stakeholders.
• Mentor QA engineers in SQL, healthcare data validation, troubleshooting, and QA best practices.
• Identify opportunities to use AI and automation for data validation, anomaly detection, test generation, SQL assistance, and QA process improvement.
• Ensure QA activities comply with HIPAA, privacy, security, and PHI/PII handling requirements.

Qualifications

• Strong QA experience with healthcare data, EHR/EMR applications, integrations, and database testing.
• SME-level knowledge and hands-on experience with Epic and/or Oracle Health (Cerner), including clinical workflows, data structures, and healthcare data relationships.
• Advanced SQL and database validation skills, including complex joins, reconciliation, and large-volume data analysis.
• Strong experience with end-to-end data validation, source-to-target reconciliation, data mapping, transformation testing, and data integrity validation.
• Strong understanding of healthcare workflows and patient, provider, encounter, clinical, laboratory, and financial data.
• Knowledge of HL7, CCD/C-CDA, FHIR, XML, JSON, APIs, and healthcare interoperability.
• Strong analytical, troubleshooting, and root cause analysis skills.
• Experience leading QA activities and mentoring QA engineers.
  • Working knowledge of AI/Generative AI and AI-assisted QA techniques is preferred.