Laboratory Data Strategy & Architecture Lead

Lead laboratory data strategy, architecture, and migration planning for a complex pharmaceutical transformation. FormativGroup partners with organizations to solve complex business and technology challenges through modern application, cloud, data, AI, and digital transformation solutions. As a Laboratory Data Strategy & Architecture Lead, you will provide strategic and technical guidance for laboratory data across systems and platforms in a regulated pharmaceutical environment. You will own data strategy and roadmaps, guide mapping and conversion planning, and establish governance, quality, and integration requirements in partnership with laboratory, business, and technology stakeholders. What You'll Work On As Laboratory Data Strategy & Architecture Lead, you will: Develop and lead laboratory data strategies, roadmaps, mapping approaches, and conversion plans aligned to business and technology objectives. Define data reconciliation processes, quality standards, validation rules, and controls to support accurate and complete data migration. Establish data ownership, stewardship, governance, metadata, master/reference data, and operational handover requirements. Define laboratory data architecture, data models, integration patterns, interfaces, and cross-platform migration requirements. Partner with laboratory systems teams, data architects, business stakeholders, and delivery teams to identify dependencies, risks, gaps, and remediation plans. Provide subject matter guidance on laboratory data structures, workflows, and system transitions in regulated pharmaceutical environments. Support connected analytics, reporting, and cloud data initiatives while aligning practices with applicable regulatory and compliance requirements. What You'll Bring You will likely be successful in this role if you have: Extensive experience with laboratory systems and data in pharmaceutical or life sciences environments. Demonstrated ownership of laboratory data strategy, roadmaps, data architecture, and cross-system transformation planning. Direct experience with data mapping, conversion, migration planning, reconciliation, and data-quality controls. Strong knowledge of data governance, stewardship, metadata management, and master/reference data practices. Experience defining data models, system interfaces, integration requirements, and migration or validation standards. Ability to work directly with business, laboratory, IT, and architecture stakeholders and turn complex...

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