GxP IT Project Manager

The IT Project Manager is responsible for end-to-end delivery of GPM application, data, and integration initiatives, including sustainability/modularization efforts, technical remediation, production releases, webservices, and data archiving.

Key Responsibilities:

• planning and execution of GPM projects across the full SDLC in accordance with GxP and SDLC governance requirements.

• GPM sustainability and modularization efforts to improve long-term maintainability and speed to market.

• Partner with Quality and Compliance teams to ensure releases meet 21 CFR Part 11 requirements (electronic records, audit trails, access controls).

• Ensure integrations and webservices comply with GxP data integrity, security, and traceability requirements.

• Delivery of GPM initiatives in compliance with GxP regulations, including 21 CFR Part 11, data integrity, validation, and audit-readiness expectations.

• Support regulated environments by embedding quality, validation, and compliance controls across application, data, and integration initiatives.

• Maintain integrated project plans, RAID logs, and milestone tracking.

• data archiving initiatives align with GxP records retention, data integrity, and regulatory requirements.

• Manage cross-team impacts related to data changes, archiving, and system upgrades.

• Lead governance cadence, decision forums, and stakeholder communications.

Required Skills Experience (Enhanced)

• Experience managing IT projects in GxP-regulated environments (pharma, biotech, life sciences, or regulated manufacturing).

• Working knowledge of 21 CFR Part 11, SDLC controls, validation lifecycle, and audit expectations.

• Strong understanding of data integrity principles (ALCOA+), records retention, and compliant data archiving.

• Experience operating within controlled change management and validation governance frameworks.

Good-to-Have Skills

• Experience in Life Sciences, Pharma, or Manufacturing sectors.

• Exposure to global vendor management and offshore delivery models.

• Understanding of data migration, integration, and scheduling algorithms.

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