Manager- Quality Assurance- Data (33120)

About the Role

PANTHERx is the nation’s largest rare disease pharmacy, dedicated to providing uncompromising quality and superior health outcomes for patients living with rare and devastating diseases. We are seeking a Manager, Quality Assurance, Data to lead the data-side QA function within our enterprise Quality Assurance organization. This role owns test strategy, test planning, and test execution for data pipelines, data products, and analytics outputs, maturing the Data QA practice from basic scripting to a structured, ASTQB-aligned methodology.

Responsibilities

• Data QA Strategy & Methodology
  • Own the test strategy, test planning standards, and test execution methodology for the data QA track, aligned to ASTQB principles and the enterprise QA framework.
  • Mature the Data QA function from ad-hoc scripting to structured test plans, formal test case documentation, and regression coverage across data pipelines, transformation layers, and analytics outputs.
  • Define data quality validation checkpoints at ingestion, transformation, and delivery layers in partnership with Data & Analytics engineering leadership.
  • Operationalize governance-defined data quality dimensions (completeness, accuracy, timeliness, consistency, uniqueness) as executable test criteria in pipeline validation suites.
• Test Execution & Pipeline Validation
  • Lead the development and execution of formal test suites for Tier 1 and Tier 2 data pipelines, progressing from basic null/type/row-count checks to structured validation coverage.
  • Establish regression coverage for data pipelines, ensuring changes to pipeline logic, data models, or source systems do not introduce undetected quality regressions.
  • Partner with Data Engineering and Analytics Engineering on pipeline architecture decisions that affect validation feasibility, observability, and quality checkpoints.
  • Manage defect tracking and reporting for data quality issues, including severity classification, escalation thresholds, and root cause review cadence.
• Tooling & Automation
  • Drive the automation strategy for data pipeline validation, targeting regression and contract-based testing as primary automation surfaces.
  • Evaluate, select, and implement data QA tooling in collaboration with the Director, QA and Data & Analytics leadership (e.g., Great Expectations, dbt tests, Soda, Monte Carlo integration).
  • Establish data quality metrics reporting: pipeline validation coverage, defect rates, data quality incident trends, and escape rates reported to IT leadership.
• Cross-Functional Partnership
  • Partner with Data Governance to align validation rules with governance-defined quality standards, ensuring QA operationalizes policy rather than defining it independently.
  • Partner with Informatics to ensure data pipeline acceptance criteria are testable and actionable at intake, before work enters the data engineering delivery pipeline.
  • Participate in joint retrospectives with Data & Analytics and Governance leadership to identify upstream pipeline design or requirements failures contributing to data quality incidents.

Requirements

• 7+ years of progressive QA experience, with at least 3 years focused on data quality, data pipeline validation, or analytics QA in a structured delivery environment.
• Demonstrated experience maturing data QA practices: moving from ad-hoc scripting to formal test plans, documented test cases, and regression coverage.
• Hands-on experience with data quality testing frameworks and tooling (Great Expectations, dbt tests, Soda, or equivalent).
• Deep familiarity with data quality dimensions (completeness, accuracy, timeliness, consistency, uniqueness) and how they translate into executable validation rules.
• Experience with cloud-based data platforms (Azure, AWS, or GCP) and modern data stack environments (Databricks, Snowflake, or equivalent).
• Proven ability to lead QA teams and build adoption of structured QA methodology across peer engineering functions.
• At least 2 years in a people management or team lead capacity, with experience hiring, developing, and retaining QA practitioners.

Preferred Qualifications

• ISTQB/ASTQB certification (Foundation, Advanced, or Expert level).
• Experience in healthcare, specialty pharmacy, or regulated industries with exposure to clinical or operational data environments.
• Familiarity with data governance frameworks (DAMA-DMBOK) and experience operationalizing governance-defined quality standards in pipeline validation.
• Exposure to pipeline observability platforms (Monte Carlo, Datadog, or equivalent) and ODCS or data contract testing patterns.
• Familiarity with Databricks medallion architecture, Unity Catalog, and Delta Lake in production environments.
• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent experience.

Work Environment

This position works in a home office and professional office environment. When in-office, this role routinely uses standard office equipment such as computers, phones, photocopiers, filing cabinets, and fax machines, and communicates via MS Teams.

Physical Demands

While performing the duties of this job, the employee is regularly required to sit, see, talk, or hear. The employee frequently is required to stand; walk; use hands and fingers to handle or feel; and reach with hands and arms. Visual acuity is necessary for tasks such as reading and working with various forms of data on a screen. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions of the job.

Benefits

• Hybrid, remote, and flexible on-site work schedules.
• Comprehensive benefits package including medical, dental, vision, health savings, and flexible spending accounts.
• 401K with employer matching.
• Employer-paid life insurance and short/long-term disability coverage.
• Employee Assistance Program.
• Generous paid time off for full-time employees, with limited paid time off for part-time employees.
• Paid holidays.

Location: Pittsburgh, PA (Hybrid) | Classification: Exempt | Status: Full-Time | Reports to: Director, Quality Assurance