Quality Assurance Engineer – Health IT

Cormac Corporation•Leesburg, VA

About The Position

CORMAC is seeking a Quality Assurance Engineer to plan and execute testing for the CMS Reporting and Quality division. The role ensures that application functionality, data, quality measure outputs, and reports are accurate and ready for release. It uses automated testing within CI/CD pipelines and rigorous validation of measure logic. The engineer develops and maintains automated test suites, validates data and quality measure calculations, tests user interfaces, reports, dashboards, APIs, accessibility, authentication, and business rules, and supports user acceptance testing. The position also involves testing Databricks and Spark-based processing, verifying production fixes, preparing auditable test evidence, and evaluating AI/LLM-assisted data validation approaches. CORMAC is a federal government contractor working in public healthcare. It describes its work environment as supportive, collaborative, welcoming, and diverse, and offers flexible schedules with remote, hybrid, or fully in-person workplace options.

Requirements

  • Bachelor's degree in Computer Science, Information Technology, or a similar field.
  • Must be a U.S. Citizen.
  • Must be able to obtain a Public Trust (Tier I) Clearance.
  • At least 5 years of experience in software quality assurance and testing, including test automation.
  • Experience developing test plans, test cases, and automated regression tests.
  • Strong SQL skills and experience validating data in relational databases such as PostgreSQL.
  • Experience integrating automated tests into CI/CD pipelines such as Jenkins.
  • Experience testing in Agile teams and tracking defects.
  • Strong written and verbal communication skills, with attention to detail in a regulated environment.

Nice To Haves

  • Master's degree in a relevant field.
  • Experience validating healthcare quality measures, including electronic clinical quality measures (eCQM), claims-based measures, claims data, or ETL/ELT pipelines.
  • Experience with Section 508 and WCAG accessibility testing tools such as axe, WAVE, ANDI, JAWS, and NVDA.
  • Experience with API testing and web UI test automation frameworks.
  • Experience testing applications deployed on AWS, with Python or Scala scripting for test automation.
  • ISTQB or similar testing certification.
  • Experience testing for CMS or other federal programs.
  • Experience testing Databricks or Spark-based data pipelines.
  • Familiarity with business rules management systems such as Drools.

Responsibilities

  • Develop test plans, test cases, and test data from requirements and quality measure specifications.
  • Design, build, and maintain automated unit-support, integration, and regression test suites that run in Jenkins CI/CD pipelines.
  • Validate quality measure calculations, stored procedures, ETL/ELT outputs, and output schemas using database validation frameworks and statistical anomaly checks before release.
  • Perform content and data validation of structured case data against predefined rule sets.
  • Test Angular user interfaces, reports, dashboards, and APIs for functional correctness and usability.
  • Perform Section 508 and WCAG 2.0 Level A and AA accessibility testing with automated tools and manual methods, including keyboard-only and screen-reader testing.
  • Test HARP/IDM authentication and role-based access scenarios.
  • Log, triage, and track defects to closure with developers, and verify fixes in test, staging, and production environments.
  • Support user acceptance testing with Business Analysts and CMS stakeholders, and produce auditable test evidence packages.
  • Test externalized business rule sets, such as Drools, and database rule logic, including versioned rule regression and rule-change impact testing.
  • Validate Databricks pipeline outputs and Spark-based measure processing against expected results using automated checks.
  • Verify fixes for production incidents tracked in ServiceNow and retest them in test and staging environments.
  • Evaluate AI/LLM-assisted data validation approaches to improve testing accuracy and efficiency.

Benefits

  • Flexible work schedules.
  • Remote, hybrid, or fully in-person workplace options.
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