Supply Chain Lead, Data Architect / Modeler

Johnson & Johnson Co.; São Paulo; On-site; BRL 250,000 - 420,000; Full time

Job summary

Johnson & Johnson MedTech is seeking a Data Modeler/Data Architect to support the MedTech Supply Chain data ecosystem in São Paulo, Brazil. You will define and maintain data architectures and models across planning, sourcing, manufacturing, and logistics to enable analytics and AI solutions.

You will lead design sessions, govern modeling standards, and collaborate with data engineering teams to ensure quality, lineage, and governance.

Qualifications

• Bachelor's degree in computer science, information systems, engineering, data management or related field.
• Minimum 5 years of experience in data modeling, data architecture, data warehousing, analytics engineering or related data discipline.
• Expertise in conceptual, logical, physical, normalized, dimensional and semantic modeling techniques.
• Strong knowledge of relational databases, data warehouses, lakehouse architectures, cloud data platforms and modern data integration patterns.
• Hands-on experience with enterprise data-modeling tools such as erwin, ER/Studio, or similar, including governance, versioning and documentation.

Responsibilities

• Define and maintain target-state data architectures and data models for MedTech Supply Chain data products, analytics, reporting, and AI solutions.
• Lead discovery and design sessions with stakeholders to translate processes into scalable data structures.
• Model business entities, relationships, hierarchies, reference data, history, and key measures across domains.
• Establish and govern data-modeling standards, naming conventions, reusable patterns, and design principles.
• Lead or facilitate data architecture reviews; document trade-offs and architecture decisions.
• Partner with data engineering teams to validate conformance to models, including keys, relationships, history, quality and lineage.
• Advance metadata management, business glossary alignment, lineage, discoverability and data quality with governance teams.
• Assess source-system changes, determine downstream impacts, and guide model versioning and controlled change management.
• Identify opportunities to reduce technical debt and improve reuse, scalability, performance and cost efficiency.

Skills

Data modeling

Data architecture

Data warehousing

Analytics engineering

Cloud platforms

Databricks on Azure

Lakehouse

Data governance

Education

Bachelor’s degree in computer science, information systems, engineering, data management

Advanced degree preferred

Tools

ERwin

ER/Studio

Job description

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. Our Credo calls on us to respect the dignity of every individual and create an environment for all people to thrive. Throughout the recruitment process – from application through hiring – we are committed to providing reasonable accommodations/adjustments for qualified candidates with disabilities.

Job Function: Data Analytics & Computational Sciences
Job Sub Function: Business Intelligence
Job Category: Professional
All Job Posting Locations: São Paulo, Brazil

Job Description

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.

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 raise 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.)