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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in data governance, data architecture, and supply chain processes, with a strong focus on developing AI-ready data foundations and managing data products. Proven ability to lead cross-functional teams and influence stakeholders while translating complex data concepts into actionable business strategies.
Highest-signal resume keywords
Data GovernanceData ArchitectureSupply Chain ManagementData Quality ManagementAI Agent Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data ManagementData ModelingData OntologyKnowledge GraphsSemantic Layer DesignMaster Data ManagementData Quality PracticesConceptual Data ModelingLogical Data ModelingPhysical Data Modeling
Soft Skills
Stakeholder ManagementInfluencing SkillsExecutive CommunicationTeam LeadershipCross-Functional Collaboration
Tools & Technologies
AI Agent RegistryAutomation PlatformsRDFOWLMulti-Agent Interoperability
Certifications & Qualifications
Relevant Certifications in Data and AI
Industry Keywords
Integrated Supply ChainDigital TransformationManufacturingOperationsData Governance Frameworks
Tech Stack
Tools & technologiesRPA
About the role
Key responsibilities & impact- Establish and drive the data foundation for the end-to-end Integrated Supply Chain Digital Transformation agenda
- Own data governance, ownership, and stewardship across plan, source, make, deliver, and return supply chain domains
- Define and enforce common data standards, taxonomies, master data, and reference data across ISC systems and processes
- Lead data quality management, monitoring, issue resolution, and continuous improvement
- Design and evolve enterprise-grade conceptual, logical, and physical supply chain data models
- Lead delivery and management of reusable, business-aligned data products
- Develop and maintain a contextualized ISC data ontology/semantic layer
- Enable knowledge graph and semantic capabilities for analytics, natural-language query, and AI/agentic use cases
- Define and govern standards, lifecycle stages, quality gates, and registration requirements for all ISC AI agents
- Establish and maintain a centralized AI Agent Registry/Catalog
- Ensure agents consume governed data products and the ISC ontology/semantic layer
- Define agent consistency, risk tiering, access management, observability, documentation, versioning, and interoperability standards
- Establish an agent review/certification process before production release
- Monitor agent performance, drift, redundancy, and retirement
- Publish reusable agent design patterns and reference architectures
- Ensure the data foundation is AI-ready for GenAI, predictive/prescriptive analytics, agentic AI, and automation
- Advise ISC leadership on data, AI, agent strategy, roadmap, and investment priorities
- Track and communicate ROI of data governance, AI enablement, and agent standardization initiatives, including token usage and cost optimization
- Build, lead, and develop a team of data governance, data modeling/architecture, and data product professionals
- Serve as liaison among ISC leaders, IT/Data Engineering, Enterprise Architecture, Analytics/AI, and external partners
- Influence senior stakeholders across a matrixed organization
Requirements
What you’ll need- 10+ years of experience in data management, data governance, data architecture, or analytics
- At least 5 years in supply chain, manufacturing, or operations contexts
- Proven track record leading enterprise data governance programs and data modeling initiatives at scale
- Experience building or scaling data product organizations is highly valued
- Experience with data ontology, knowledge graphs, or semantic layer design preferred
- Experience establishing or governing an AI agent inventory/registry, or equivalent governance mechanism for bots, RPA, or automation assets, strongly preferred
- Exposure to multiple agent/automation platforms with ability to define platform-agnostic standards
- Prior experience in a large-scale digital transformation program
- Deep understanding of end-to-end supply chain processes and associated data domains
- Strong knowledge of data governance frameworks, master data management, and data quality practices
- Working knowledge of conceptual, logical, and physical data modeling, data architecture, and modern data platforms
- Familiarity with ontology/semantic technologies such as RDF, OWL, and knowledge graphs
- Understanding of agentic AI architecture concepts, including tool use/function calling, orchestration, memory/context management, human-in-the-loop design, and multi-agent interoperability
- Familiarity with AI risk classification frameworks and responsible AI/model governance practices
- Ability to define technology-neutral standards across heterogeneous, multi-platform agent landscapes
- Strong stakeholder management, influencing, and executive communication skills
- Ability to translate technical data concepts into business value for non-technical audiences
- Bachelor's degree in Supply Chain, Data/Computer Science, Information Systems, Engineering, or related field required
- Relevant certifications in data and AI are a plus
Benefits
Comp & perks- Face-to-face collaboration culture
- Learning, growth, and development opportunities
- Equal opportunity employment