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Johnson and Johnson Innovative Medicine (J&J IM) needs to build and operate an enterprise data platform and governance program for R&D to make data trusted, compliant, and AI-ready, while protecting proprietary advantage and accelerating portfolio decisions.

Requirements

• Expertise in modern data architectures (lake/lakehouse/data fabric or mesh), ETL/ELT & streaming, APIs, DataOps/automation, lineage/observability.
• Demonstrated experience with ontologies/metadata, master/reference data, and catalog tools.
• Strong grasp of GxP concepts and compliance frameworks (21 CFR Part 11/Annex 11), HIPAA/GDPR, de-identification, retention/archival.

Responsibilities

• Provide thought leadership, management, and execution of strategic initiatives aimed at integration of data assets across the R&D Data Landscape
• Establish a strong data governance framework and culture to ensure data integrity, quality, and compliance.
• Partner with JJIT to map and integrate internal and relevant external data sources in the broader R&D data ecosystem (including Discovery, Development, Regulatory and TAs) into a unified architecture while protecting J&J’s proprietary data
• Make broader R&D data “AI-ready” through robust data engineering, standardization, and annotation (e.g. using consistent ontologies and data models)
• Create a sustainable pipeline of data-driven use cases with clear value, prioritized in line with strategic R&D priorities.
• Build the organizational capabilities (people, process, technology) needed to govern and scale this data strategy across the enterprise
• Partner with JJT and technology stakeholders to evaluate and select cutting-edge solutions supporting Data Platform initiatives and processes.

Other

• Prior leadership of multi-disciplinary teams and vendor/partner ecosystems
• Proven ownership of enterprise-scale data platforms and governance programs (federated models, stewardship, policy, and quality).
• Exceptional stakeholder management and executive communication skills;
• Ability to influence and drive change in a complex organizational environment.
• Strong analytical and problem-solving skills, with the ability to assess and manage data-related risks.