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Vanguard · 19 hours ago

Chief Data Architect

Charlotte, NC

Full-time

Hybrid

Director/Executive

Vanguard is aiming to become an AI-driven organization, and they are seeking a Chief Data Architect to lead the newly created Enterprise Data Architecture function. This role is crucial for defining, aligning, and governing enterprise-wide data architecture strategies that enhance data and analytics capabilities across the organization.

FinanceFinancial Services

No H1B

Responsibilities

Define data domains, subdomains, and key data subject areas across Vanguard

Design and evolve enterprise-level semantic data models, including logical and conceptual models, ontologies, and domain definitions

Lead the standardization of metadata practices across domains, enabling discoverability, lineage, and governance

Partner with product, data, and engineering teams to define domain-driven data contracts that support AI, analytics, and operational needs

Architect and implement reusable taxonomy and ontology frameworks that align business meaning with technical implementation

Enable scalable and interoperable semantic layers across data platforms (e.g., Lakehouse, Knowledge Graphs, Data Warehouses)

Collaborate with governance, AI/ML, and metadata teams to support computational governance and automated metadata enrichment

Provide strategic guidance on data modeling techniques (3NF, dimensional, Data Vault, RDF/OWL) and drive adoption of best practices

Qualification

Data modelingOntology engineeringMetadata architectureSemantic web standardsDomain-driven designData mesh principlesKnowledge graph architectureCollaboration skillsClear communication

Required

Deep expertise in data modeling (conceptual, logical, physical), ontology engineering, and metadata architecture

Proficient in tools such as Collibra, Alation, Atlan, FINOS Legend, Erwin, Lucidchart, AtScale, Stardog, TopBraid, Protégé, or other semantic/metadata platforms

Knowledge of semantic web standards (RDF, OWL, SKOS, SPARQL) and their practical application in enterprise data ecosystems

Familiarity with domain-driven design, data mesh principles, and knowledge graph architecture

Experience integrating business glossaries, taxonomies, and metadata systems into data platforms and AI pipelines

Ability to bridge business needs with technical architecture using clear, model-driven communication

Strong collaboration skills, working cross-functionally with data product owners, engineers, data scientists, and governance teams