Enterprise Data Architect (Ontology and Semantic Modeling)

Responsibilities

• Define and implement enterprise ontologies, taxonomies, and controlled vocabularies aligned to core business domains
• Design a semantic context layer that connects structured data, metadata, and business meaning
• Establish patterns and standards for knowledge graph development and semantic modeling
• Align semantic architecture with an existing data platform, including Snowflake, and support emerging artificial intelligence and agent-based use cases
• Integrate data governance artifacts such as definitions, lineage, ownership, and classification into semantic models to enable executable governance
• Introduce and standardize metadata frameworks that enrich data for automation and downstream analytics
• Ensure data governance and architecture initiatives evolve in parallel and remain tightly aligned
• Provide guidance on transitioning from siloed systems to a centralized, enterprise-wide data architecture
• Identify and address gaps in data modeling, semantic integration, and knowledge representation
• Develop reference architectures, reusable design patterns, and best practice documentation for internal adoption
• Collaborate closely with data architects, engineers, and governance teams to transfer knowledge and build internal capability
• Create playbooks, standards, and documentation that enable long-term sustainability after engagement completion
• Define clear handoff milestones and exit criteria to ensure continuity
• Support executive stakeholders by translating complex technical concepts into clear, business-focused narratives
• Help articulate the value of semantic architecture and its impact on data strategy and artificial intelligence readiness

Required experience and skills

• 10 or more years of experience in data architecture, ontology design, taxonomy development, or metadata management
• Strong expertise in semantic modeling frameworks such as OWL, RDF, SKOS, or equivalent approaches
• Experience designing and implementing enterprise-scale taxonomies and controlled vocabularies
• Proven ability to define and operationalize metadata standards across multiple systems and business units
• Background in financial services or similarly complex, multi-entity environments
• Experience leading data governance and master data initiatives, including stakeholder alignment and data landscape analysis
• Familiarity with modern data platforms such as Snowflake and knowledge graph architectures
• Understanding of artificial intelligence and agent-based systems in relation to data architecture
• Strong documentation and communication skills, with the ability to produce reusable standards, frameworks, and architectural guidance
• Ability to operate at both strategic and hands-on levels, guiding implementation while advising leadership
• Experience mentoring and enabling internal teams through coaching, pairing, and knowledge transfer