Senior Data Modeler

This is a fully remote position, open to applicants in United States, +2 more locations.

📋 Description

• Architect and manage data structures for unstructured knowledge assets throughout the Knowledge Management ecosystem.

• Create both logical and physical data models for unstructured and semi-structured content derived from KM pipelines.

• Define the boundaries and ownership for various data products.

• Set metadata standards and tagging taxonomies to ensure consistent classification across knowledge sources.

• Assign and implement security and sensitivity classifications in accordance with data governance, privacy, and legal/risk regulations.

• Register, document, and sustain data products in Databricks Unity Catalog, which includes schemas, access permissions, lineage, and catalog-level metadata.

• Collaborate with data engineers to synchronize ingestion, transformation, and storage strategies with the designed domain structures.

• Work together with Knowledge Products, Research Products, and Architecture/Data/Technology stakeholders to address downstream consumption requirements.

• Assist in privacy and legal review processes through the classification and documentation of data products.

• Develop repeatable modeling standards and playbooks for upcoming data products.

• Deliver a domain model and metadata taxonomy that is embraced for at least one significant KM data product line.

• Ensure data products are easily discoverable in Unity Catalog with appropriate security classifications.

• Minimize the turnaround time for privacy/legal classification reviews.

⛳️ Requirements

• A minimum of 7 years of experience in data modeling, information architecture, or enterprise data architecture (mandatory skills).

• Extensive experience in designing conceptual, logical, and physical data models for enterprise data platforms.

• Deep understanding of entities, relationships, metadata, master/reference data, and data lineage.

• Familiarity with taxonomy, ontology, semantic models, and controlled vocabularies.

• Practical experience with Databricks, Delta Lake, and Unity Catalog or similar modern data platforms.

• Capability to convert business concepts and unstructured information into structured, reusable data models.

• Experience in designing knowledge graphs, ontologies, and semantic knowledge models (desired).

• Knowledge of GenAI/RAG knowledge models and vector/embedding representations (desired).

• Experience in modeling documents, document elements, entities, relationships, evidence, and provenance (desired).

• Understanding of Neo4j, RDF, or property graphs (desired).

• Experience with Commercial/Customer/CRM domain models, SharePoint content, or enterprise knowledge platforms (desired).

• At least 5 years of experience in data modeling, data architecture, or information architecture, with substantial exposure to unstructured or semi-structured data.

• Direct experience in or adjacent to Knowledge Management, content management, or the enterprise search domain.

• Hands-on experience with a modern data catalog; Databricks Unity Catalog is strongly preferred.

• Proven ability to define data domains and product boundaries in a large, multi-stakeholder environment.

• Practical knowledge of metadata management, including tagging schemas, taxonomies, controlled vocabularies, or ontology design.

• Understanding of data security/sensitivity classification frameworks and access control in a lakehouse setting.

• Experience collaborating with data engineering teams on ingestion and pipeline design.

• Excellent written and verbal communication abilities.

• Familiarity with enterprise knowledge platforms such as Glean, SharePoint, or ServiceNow, or AI-enhanced retrieval systems (preferred).

• Knowledge of Databricks Delta Lake, Delta Sharing, or Lakehouse Federation (preferred).

• Previous experience in professional services, consulting, or a similar document/case-intensive knowledge environment (preferred).

• Exposure to Legal/Risk/Privacy review processes for data classification and access approvals (preferred).

• A background in library science, information science, or applied ontology is advantageous but not mandatory.

🏝️ Benefits

• Remote work: 100% remote (USA/Canada).

• Equal employment opportunities and an inclusive work environment.

• Commitment to diversity.