Senior QA & Data Governance Lead — Pharma Domain

Robotic Technologies Automation; Atlanta (GA); On-site; USD 150,000 - 210,000; Full time

Job summary

Robotic Technologies Automation is seeking a senior expert to lead quality management across pharma data operations in the Atlanta area. The role focuses on designing and scaling quality frameworks, data governance, and compliance programs to support large-scale analytics initiatives.

The ideal candidate brings 12+ years in quality and data operations within life sciences, with hands-on experience in CAPA, audits, and end-to-end data quality improvement across complex environments.

Qualifications

• 12+ years of experience in Quality Management, Data Governance, Data Quality, or Pharma Data Operations.
• Experience designing and implementing quality frameworks from the ground up.
• Experience managing quality programs for large data and analytics organizations.
• Experience in pharmaceutical, biotechnology, life sciences, or healthcare industries.

Responsibilities

• Develop and implement end-to-end quality management programs for pharma data.
• Oversee CAPA processes and audit readiness.
• Ensure data governance and quality controls across data lifecycles.
• Collaborate with cross-functional teams to maintain compliance.

Skills

Quality Management

Quality Framework Design

Quality Assurance (QA)

Quality Control (QC)

CAPA Management

Audit & Compliance Management

Process Excellence Data & Analytics

Data Quality Management

Data Governance

Data Lineage

Metadata Management

Data Validation Frameworks

Master Data Management (MDM) PharmaPh

Job description

Robotic Technologies Automation is seeking a senior expert to lead quality management across pharma data operations in the Atlanta area. The role focuses on designing and scaling quality frameworks, data governance, and compliance programs to support large-scale analytics initiatives.

The ideal candidate brings 12+ years in quality and data operations within life sciences, with hands-on experience in CAPA, audits, and end-to-end data quality improvement across complex environments.