What are the responsibilities and job description for the Data Modeler position at Q1 Technologies, Inc.?
Job Description:
Role - Data Modeler
Experience Required -10 Years
Must Have Technical/Functional Skills
• Knowledge of ACORD insurance standards.
• Experience with ontology and semantic modeling platforms such as Timbr, TopBraid, PoolParty, or Stardog.
• Experience with graph databases such as Neo4j, Stardog, or Amazon Neptune.
• Familiarity with data governance and metadata platforms such as Collibra, Alation, or Microsoft Purview.
• Exposure to AI/GenAI, semantic search, or enterprise knowledge graph initiatives.
Ontology Data Modeler, Semantic Data Modeler, Data Modeler, Knowledge Graph, Enterprise Ontology, Semantic Modeling, Insurance Data Architect, RDF, OWL, SPARQL, ACORD, Neo4j, Stardog, Amazon Neptune, Snowflake, Databricks, AWS, Azure.
Roles & Responsibilities
• Develop conceptual, logical, and physical data models for enterprise data platforms.
• Design and maintain enterprise ontologies, semantic data models, knowledge graphs, taxonomies, and business vocabularies.
• Define business entities, relationships, hierarchies, and semantic rules across enterprise data domains.
• Collaborate with business and technical stakeholders to translate business requirements into scalable data and semantic solutions.
• Model insurance domains including Policy, Claims, Underwriting, Customer, Product, Billing, and Producer/Agency.
• Support data governance, metadata management, data lineage, and data quality initiatives.
• Ensure alignment with enterprise architecture, industry standards, and data governance best practices.
Generic Managerial Skills, If any
Key Responsibilities
• Develop conceptual, logical, and physical data models for enterprise data platforms.
• Design and maintain enterprise ontologies, semantic data models, knowledge graphs, taxonomies, and business vocabularies.
• Define business entities, relationships, hierarchies, and semantic rules across enterprise data domains.
• Collaborate with business and technical stakeholders to translate business requirements into scalable data and semantic solutions.
• Model insurance domains including Policy, Claims, Underwriting, Customer, Product, Billing, and Producer/Agency.
• Support data governance, metadata management, data lineage, and data quality initiatives.
Ensure alignment with enterprise architecture, industry standards, and data governance best practices.