Manager- Quality Assurance- Data

7,000 Diseases - 500 Treatments - 1 Rare Pharmacy

PANTHERx is the nation’s largest rare disease pharmacy, and we put the patient experience at the top of everything that we do.

If you are looking for a career in the healthcare field that embraces authentic dedication to patient care, you don’t need to look beyond PANTHERx. In every line of service, in every position and area of expertise, PANTHERx associates are driven to provide the highest quality outcomes for our patients.

We are seeking team members who:

Are inspired and compassionate problem solvers;

Produce high quality work;

Thrive in the excitement of the ever-challenging environment of modern medicine; and

Are committed to achieving superior health outcomes for people living with rare and devastating diseases.

At PANTHERx, we know our employees are the driving force in what we do. We cultivate talent and encourage growth within PANTHERx so that our associates can continue to explore their interests and expand their careers. Guided by our mission to provide uncompromising quality every day, we continue our strategic growth to further reach those affected by rare diseases.

Join the PANTHERx team, and define your own RxARE future in healthcare!

Location: Pittsburgh, PA (Hybrid)

Classification: Exempt

Status: Full-Time

Reports to: Director, Quality Assurance

Purpose

The Manager, Quality Assurance, Data leads the data-side QA function within the enterprise Quality Assurance organization, owning test strategy, test planning, and test execution for data pipelines, data products, and analytics outputs. This role is responsible for maturing the Data QA practice from basic scripting to structured, ASTQB-aligned methodology: formal test plans, documented test cases, regression coverage, and measurable data quality validation against governance-defined quality dimensions. The Manager works in close partnership with Data & Analytics and Data Governance to embed validation checkpoints across the full data lifecycle.

Responsibilities

Data QA Strategy & Methodology

• Owns the test strategy, test planning standards, and test execution methodology for the data QA track, aligned to ASTQB principles and the enterprise QA framework.
• Matures 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.
• Defines data quality validation checkpoints at ingestion, transformation, and delivery layers in partnership with Data & Analytics engineering leadership.
• Operationalizes governance-defined data quality dimensions (completeness, accuracy, timeliness, consistency, uniqueness) as executable test criteria in pipeline validation suites.

Test Execution & Pipeline Validation

• Leads 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.
• Establishes regression coverage for data pipelines, ensuring that changes to pipeline logic, data models, or source systems do not introduce undetected quality regressions.
• Partners with Data Engineering and Analytics Engineering on pipeline architecture decisions that affect validation feasibility, observability, and quality checkpoints.
• Manages defect tracking and reporting for data quality issues, including severity classification, escalation thresholds, and root cause review cadence.

Tooling & Automation

• Drives the automation strategy for data pipeline validation, targeting regression and contract-based testing as primary automation surfaces.
• Evaluates, selects, and implements data QA tooling in collaboration with the Director, QA and Data & Analytics leadership (e.g., Great Expectations, dbt tests, Soda, Monte Carlo integration).
• Establishes data quality metrics reporting: pipeline validation coverage, defect rates, data quality incident trends, and escape rates reported to IT leadership.

Cross-Functional Partnership

• Partners with Data Governance to align validation rules with governance-defined quality standards, ensuring QA operationalizes policy rather than defining it independently.
• Partners with Informatics to ensure data pipeline acceptance criteria are testable and actionable at intake, before work enters the data engineering delivery pipeline.
• Participates in joint retrospectives with Data & Analytics and Governance leadership to identify upstream pipeline design or requirements failures contributing to data quality incidents.

Required Qualifications

• 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 communications 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 are available, based on the position. PANTHERx Rare Pharmacy also affords an excellent benefit package, including but not limited to medical, dental, vision, health savings and flexible spending accounts, 401K with employer matching, employer-paid life insurance and short/long term disability coverage, and an Employee Assistance Program! Generous paid time off is also available to all full-time employees. Of course we offer paid holidays too!

Equal Opportunity:

PANTHERx Rare Pharmacy is an equal opportunity employer, and does not discriminate in recruiting, hiring, promotions or any term or condition of employment based on race, age, religion, gender, ethnicity, sexual orientation, gender identity, disability, protected veteran's status, or any other characteristic protected by federal, state or local laws.