Life Sciences Quality Transformation Manager

EY

Dallas (TX)

On-site

USD 128,000 - 257,000

Full time

8 days ago

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Job summary

EY is seeking a Client-facing Life Sciences Manufacturing Quality Manager to lead technology-enabled workstreams across quality systems, data, AI, and delivery in regulated environments. You will guide assessments, requirements, design, testing, and adoption while ensuring inspection readiness and CAPA effectiveness.

The role emphasizes collaboration with quality, QA/QC, manufacturing, laboratory, MS&T, IT, and vendors, with heavy travel and strong governance.

Qualifications

A bachelor’s degree in life sciences, engineering, quality, supply chain, information systems, business, or related discipline.
At least 7 years of relevant Life Sciences Manufacturing Quality experience, QA/QC, quality technology, industrial data and AI, technology consulting, or related fields.
Experience leading a client-facing quality, digital, data, or technology workstream through design and at least one implementation or deployment phase.
Experience in pharmaceutical, biotechnology, medical-device, or comparably regulated manufacturing environments.
Ability to translate quality-domain needs into process, functional, data, integration, or testing deliverables and coordinate business and technical contributors.
Knowledge of GxP/GMP and documentation, change-control, data-integrity, and electronic-records-and-signatures considerations.

Responsibilities

Lead client-facing workstreams in Life Sciences Manufacturing Quality transformation with ownership of plans, deliverables, risks, decisions, and outcomes.
Assess current-state quality processes, user needs, system landscapes, data flows, performance gaps, and site constraints.
Translate priorities into process designs, requirements, acceptance criteria, and measurable improvements.
Develop functional designs for deviations/nonconformances, CAPA, change control, complaints, audits, and inspection readiness.
Coordinate integration requirements across eQMS/QMS, LIMS, MES/MOM, ERP, document-management, and lab systems.
Define and review data mappings, master-data needs, interface specifications, and data-quality controls for reporting and AI use cases.
Help deliver quality analytics and AI use cases with data readiness, workflow fit, and governance considerations.
Work with validation teams to reflect GxP, data-integrity, and electronic-records requirements in deliverables.
Oversee configuration, testing, deployment readiness, training, and handover for workstreams.
Facilitate cross-team sessions; manage scope, schedule, resources, quality, and risks.
Coach junior team members and capture reusable requirements and delivery lessons.