Lead, Data Context & AI Enablement

Johnson & Johnson Innovative Medicine; Hopewell Township (OH); Hybrid; USD 137,000 - 236,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Life insurance

401(k) plan

Long‑term incentive

Job summary

Johnson & Johnson is seeking an Associate Director, Data Context Enablement to lead the Data Context Layer strategy and governance across therapeutic areas. This role will define reusable data context products, semantic models, and standards to accelerate GenAI, agentic workflows, analytics, CRM, field reporting, forecasting, and decision support.

The leader will align with business and technology teams, operationalize data context services on enterprise platforms, and establish AI governance

Qualifications

• 10+ years of experience in data management, AI, analytics, semantic technologies, knowledge management, data platforms, enterprise architecture, or related technology areas.
• Undergraduate degree or equivalent experience in Computer Science, Data Science, Information Systems, Engineering, Business, Analytics, Health Sciences, or a related field; master’s degree preferred.
• Strong understanding of data platforms, semantic layers, data governance, metadata management, and enterprise data lifecycle management.
• Knowledge of Generative AI, Large Language Models, retrieval‑augmented generation, agentic AI, semantic modeling, metadata management, and AI governance.
• Experience implementing AI governance, data governance, metadata governance, or semantic governance frameworks.
• Experience leading complex cross‑functional data, analytics, platform, or AI initiatives and building reusable enterprise data or AI capabilities.
• Proven ability to partner with senior leaders, business stakeholders, technology teams, and external vendors.
• Strong communication, problem‑solving, relationship‑building, and program management skills, with the ability to translate complex AI and data topics into clear business value.
• Familiarity with data privacy, compliance, information security, and responsible AI considerations in a regulated industry.
• Experience in pharmaceutical, healthcare, or life sciences domains.

Responsibilities

• Lead the Data Context Layer strategy, roadmap, and operating model across therapeutic areas as a foundational capability of the Data organization.
• Define and scale reusable data context products, services, semantic models, knowledge assets, and standards that accelerate GenAI, agentic workflows, analytics, CRM, field reporting, forecasting, and decision support.
• Partner with business and technology teams to identify high‑value AI use cases and ensure consistent use of approved definitions, governed metrics, and trusted sources.
• Operationalize data context services within enterprise Data and AI platforms, ensuring alignment with data architecture, governance, metadata, and quality standards.
• Establish context governance processes, quality measures, lifecycle standards, and responsible AI controls to manage semantic drift, outdated knowledge and inconsistent definitions.
• Evaluate emerging AI, semantic, knowledge management, and external data capabilities that advance enterprise data and AI strategy.
• Ensure the role advances the Data organization’s mission to deliver trusted, connected, reusable, and AI‑ready data capabilities for enterprise decision‑making.

Skills

Generative AI

Agentic AI

AI Context Engineering

AI Governance

Responsible AI

Semantic modeling

Ontology management

Knowledge graphs

Knowledge management

Metadata management

Education

Bachelor's degree or equivalent

Master's degree preferred

Job description

Johnson & Johnson is seeking an Associate Director, Data Context Enablement to lead the Data Context Layer strategy and governance across therapeutic areas. This role will define reusable data context products, semantic models, and standards to accelerate GenAI, agentic workflows, analytics, CRM, field reporting, forecasting, and decision support.

The leader will align with business and technology teams, operationalize data context services on enterprise platforms, and establish AI governance