Data Modeling Specialist

4 days ago


Richmond, California, United States Capital One Full time
About the Role

The Data Modeling Specialist will be responsible for developing and implementing enterprise ontologies to support data strategies. This involves collaboration across finance and technology teams to create standardized data practices and advocate for the use of semantic technology.

The role requires leading a team focused on data modeling, ontology governance, and aligning technology with business objectives. The ideal candidate will have a strong understanding of W3C standards and ontology tools such as Protégé and TopQuadrant.

Key Responsibilities:

  • Define clear and actionable problem statements to help teams deliver results while displaying a comprehensive understanding of ontologies and optimized data models.
  • Leverage customer insights to influence priorities and roadmap development while advocating for and driving alignment between stakeholders in the development of acceptance criteria.
  • Own and prioritize the near-term Ontology and Data Modeling roadmap to deliver on business outcomes, quickly identifying points of leverage in complex problems or systems, and utilizing data effectively to define success metrics and measurable outcomes.
  • Utilize balanced judgment in decisions about risks of both actions taken and not taken while innovating on ways to iterate faster in a well-managed way for the immediate team.

Requirements:

  • Bachelor's degree in information science, computer science, engineering, library science, ontology, semantics or computational linguistics.
  • At least 4 years' experience in a metadata field of work (ontology, taxonomy, semantics or computational linguistics).
  • At least 4 years' experience or training in using W3C standards including linked and canonical data and ontologies (JSON, XML, RDF, RDFS, OWL, and SKOS).
  • At least 4 years' experience or training in ontology and linked data tools (Protégé, TopQuadrant, PoolParty, Stardog, AnzoGraph, Neptune, or )
  • At least 4 years' experience or training with SQL or SPARQL.


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