Supply Chain Lead, Data Architect / Modeler

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s):

Remember, whether you apply to one or all of these requisition numbers, your applications will be considered as a single submission.

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About MedTech

Fueled by innovation at the intersection of biology and technology, we’re developing the next generation of smarter, less invasive, more personalized treatments.

Your unique talents will help patients on their journey to wellness. Learn more at https://www.jnj.com/medtech

We are searching for the best talent for a Data Modeler / Data Architect to support the MedTech Supply Chain data ecosystem

Purpose: Reporting to the Senior Manager, Architecture, this role will define and govern scalable data models and domain data architectures that support trusted data products, analytics, reporting, and AI capabilities.

The Data Modeler / Data Architect will partner closely with business, data product, engineering, governance, analytics, AI, and enterprise architecture teams. The role is accountable for translating business processes and information requirements into conceptual, logical, physical, dimensional, and semantic models; establishing reusable modeling standards and architecture patterns; and providing design oversight through implementation.

Key Responsibilities

• Define and maintain target-state domain data architectures and conceptual, logical, physical, dimensional, and semantic data models for MedTech Supply Chain data products, analytics, reporting, and AI solutions.
• Lead discovery and design sessions with business and technology stakeholders to translate supply chain processes and information needs into scalable, reusable data structures.
• Model business entities, relationships, hierarchies, reference data, history, and key measures across planning, sourcing and procurement, manufacturing, quality, inventory, logistics, distribution, customer service, and order fulfillment domains.
• Establish and govern data-modeling standards, naming conventions, reusable patterns, and design principles across source, ingestion, transformation, semantic, and consumption layers.
• Lead or facilitate data architecture and model reviews; recommend design decisions, document trade-offs and architecture decisions, and escalate material risks or exceptions to the Senior Manager, Architecture.
• Partner with data engineering teams through build and deployment to validate conformance to approved models, including keys, relationships, history, performance, security, access, quality, and lineage requirements.
• Advance metadata management, business glossary alignment, lineage, discoverability, data quality, and traceability in partnership with data governance and business data owners.
• Assess source-system and business-process changes, determine downstream impacts, and guide model versioning, migration, and controlled change management.
• Identify opportunities to rationalize overlapping structures, reduce technical debt, and improve reuse, scalability, performance, and cost efficiency across the data ecosystem.
• Provide technical guidance and coaching to modelers, engineers, analysts, and data product teams while promoting consistent architecture practices and shared accountability for data quality.

Qualifications

• A minimum of a Bachelor’s degree in computer science, information systems, engineering, data management, or a related discipline is required; an advanced degree is preferred.
• A minimum of 5 years of relevant experience in data modeling, data architecture, data warehousing, analytics engineering, or a related data discipline is required, including ownership of complex enterprise or domain-level designs.
• Demonstrated expertise in conceptual, logical, physical, normalized, dimensional, and semantic modeling techniques is required.
• Strong knowledge of relational databases, data warehouses, lakehouse architectures, cloud data platforms, and modern data integration patterns is required.
• Hands-on experience with enterprise data-modeling tools such as erwin, ER/Studio, or similar, including model governance, versioning, and documentation, is required.
• Working knowledge of metadata, lineage, data quality, master and reference data, security, access controls, and data-governance practices is required.
• Experience leading architecture or design reviews, communicating trade-offs, and influencing decisions across business and technical teams without direct authority is required.
• Demonstrated ability to translate complex business processes and requirements into clear, implementable architecture and model deliverables is required.
• Strong written and verbal communication, facilitation, critical-thinking, and problem-solving skills, with the ability to engage technical and non-technical audiences, are required.
• Demonstrated ability to operate independently, manage competing priorities, and collaborate across architecture, engineering, data product, governance, analytics, AI, and business teams is required.

Preferred Skills

• Databricks on Azure, medallion or lakehouse architecture patterns, and cloud-based data engineering ecosystems
• Semantic-layer design, reusable data products, and governed data assets for analytics and AI use cases
• MedTech, manufacturing, regulated environments, or end-to-end supply chain data and business processes
• SAP S/4HANA or other enterprise resource planning data structures and their integration with analytical platforms
• Data catalogs, business glossaries, observability, privacy, compliance, and architecture-repository tools
• Relevant certification in data management, cloud architecture, Databricks, Azure, or enterprise architecture

Other

• This position may require up to 10% domestic or international travel based on business needs.
• The anticipated job function, job sub-function, level, and final position title should be confirmed with Human Resources and the hiring organization prior to posting.

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