Director, Research Data Foundation

Johnson & Johnson

. Lead research data technology capabilities enabling trusted, governed, and reusable data across the Research organization .

Posted 10/12/2026full-timeUnited StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading research data technology capabilities, ensuring the implementation of FAIR principles and effective data governance. Proficient in designing scalable data platforms and managing multi-functional teams to drive data quality and operational excellence.

Highest-signal resume keywords

Research Data Platform EngineeringFAIR Data PrinciplesLaboratory InformaticsData Governance WorkflowsCloud-Based Data Solutions

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionMetadata EnrichmentPipeline EngineeringData VirtualizationData Quality FrameworksSemantic StandardsMaster/Reference Data SolutionsData Product ManagementOperational MetricsIssue Remediation

Soft Skills

Outstanding Communication SkillsExecutive Influencing SkillsTeam LeadershipCollaboration

Certifications & Qualifications

Master’s Degree in Computer Science or Life Sciences

Industry Keywords

Research Data ManagementData ServicesAI-Ready DataGoverned Data AssetsData Product Lifecycle Management

Tech Stack

Tools & technologies

CloudCyber Security

About the role

Key responsibilities & impact

Lead research data technology capabilities enabling trusted, governed, and reusable data across the Research organization
Drive transformation of research data from fragmented systems, instruments, labs, and scientific workflows into a FAIR environment
Partner with research functions, lab informatics teams, data product owners, scientists, data science/modeling teams, governance leaders, architecture, cybersecurity, and technology platform teams
Translate research strategy, FAIR principles, scientific data needs, and AI-readiness requirements into scalable platforms, metadata practices, data services, standards, scorecards, and operating routines
Lead scalable data ingestion and curation platforms, including onboarding, metadata enrichment, pipeline engineering, orchestration, monitoring, and issue resolution
Enable governed and performant access to distributed R&D data through integration and data virtualization
Define and operate research data quality and FAIR frameworks, standards, thresholds, and executive reporting
Establish quality rules, ownership, metadata expectations, and FAIR acceptance criteria
Translate quality and FAIR insights into remediation priorities and measurable improvement roadmaps
Lead research data catalog, metadata, ontology, lineage, and master/reference data capabilities
Establish canonical research entities, identifiers, controlled vocabularies, semantic standards, metadata, lineage, and provenance across research platforms and workflows
Enable semantically consistent research data across compounds, targets, assays, samples, studies, experiments, instruments, and other scientific domains

Requirements

What you’ll need

Master’s degree or equivalent experience in Computer Science or Life Sciences
10+ years of progressive technology leadership experience with relevant focus
Experience in research data platform engineering, scientific data architecture, laboratory informatics, or enterprise research data management
Experience designing and implementing cloud-based FAIR data environments, semantic and metadata capabilities, and enterprise master/reference data solutions
Understanding of FAIR data principles, data product management, data contracts, research governance workflows, privacy, security, compliance, AI-ready data, and platform operating models
Success leading multi-functional teams and influencing research leaders and scientists
Outstanding communication skills to translate complex data platform and governance topics into clear business decisions and outcomes
Success building and operating enterprise-grade data solutions
Experience establishing operating models for governed, reusable data assets
Ability to partner with scientists, data science, analytics, business, and technology organizations
Experience handling critical data services with reliability targets, operational metrics, issue remediation, cost optimization, and service improvement routines
Track record driving adoption of shared platforms, common standards, self-service patterns, metadata practices, governance workflows, and data product lifecycle management
Strong executive influencing skills

Benefits

Comp & perks

Inclusive work environment
Equal employment opportunity
Inclusive interview process and disability accommodations