Senior Manager - AI-Ready Information Architecture

Johnson & Johnson Innovative Medicine; New Jersey; On-site; USD 140,000 - 190,000; Full time

Job summary

Johnson & Johnson Innovative Medicine Supply Chain seeks a Senior Manager of IMSC Information Architecture Make/Quality to design semantic data models and set IA standards. You will ensure data assets are FAIR, align models with enterprise architecture, and support analytics, automation, and AI initiatives.

Responsibilities include building business context layers linking metadata, taxonomies, ontologies, and knowledge graphs, and collaborating with governance and technology teams to implement

Qualifications

• Extensive experience in information and data architecture, preferably in regulated healthcare, life sciences, or supply chain.
• Strong expertise in semantic modeling, metadata management, knowledge graphs.
• Experience with platforms like Alation, Neo4j, or Databricks.
• Ability to translate complex business needs into structured data models.
• Excellent stakeholder collaboration across global teams.

Responsibilities

• Design and oversee semantic and conceptual data models.
• Establish IA standards and ensure data assets are FAIR.
• Align information models with enterprise architecture.
• Support analytics, automation, and AI initiatives.
• Develop business context layers connecting metadata, taxonomies, ontologies, and knowledge graphs.
• Collaborate with Data Owners, Governance, and Technology teams.

Skills

Information architecture

Semantic modeling

Metadata management

Knowledge graphs

Alation

Neo4j

Databricks

FAIR compliance

ISO standards

Tools

Alation

Neo4j

Databricks

Job description

Johnson & Johnson Innovative Medicine Supply Chain seeks a Senior Manager of IMSC Information Architecture Make/Quality to design semantic data models and set IA standards. You will ensure data assets are FAIR, align models with enterprise architecture, and support analytics, automation, and AI initiatives.

Responsibilities include building business context layers linking metadata, taxonomies, ontologies, and knowledge graphs, and collaborating with governance and technology teams to implement