Staff Engineer

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

📋 Description

• Design and oversee the data architecture for unstructured knowledge assets within the client's Knowledge Management ecosystem.

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

• Identify domain boundaries and ownership responsibilities for data products.

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

• Implement and uphold security and sensitivity classifications in accordance with data governance, privacy, and legal/risk requirements.

• Register, document, and maintain data products within Databricks Unity Catalog, which includes schemas, access grants, lineage, and catalog-level metadata.

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

• Work closely with stakeholders from Knowledge Products, Research Products, and Architecture/Data/Technology to address downstream consumption needs.

• Assist in privacy and legal review processes by ensuring data products are properly classified and documented.

• Establish repeatable modeling standards and playbooks to facilitate the onboarding of future data products.

• Define and implement a domain model and metadata taxonomy for at least one significant KM data product line.

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

• Streamline the privacy/legal classification review process by maintaining consistent metadata and tagging.

⛳️ 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.

• Strong grasp of entities, relationships, metadata, master/reference data, and data lineage.

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

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

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

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

• Familiarity with GenAI/RAG knowledge models and vector/embedding representations.

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

• Knowledge of Neo4j, RDF, or property graphs.

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

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

• Direct experience in or related to Knowledge Management, content management, or enterprise search.

• Practical experience with a modern data catalog; Databricks Unity Catalog is strongly preferred.

• Proven ability to define data domains and boundaries for data products in a large, multi-stakeholder organization.

• Solid understanding of metadata management, including tagging schemas, taxonomies, controlled vocabularies, or ontology design.

• Familiarity with data security/sensitivity classification frameworks and access control in a lakehouse environment.

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

• Excellent written and verbal communication skills.

• Experience with enterprise knowledge platforms such as Glean, SharePoint, or ServiceNow, or AI-powered retrieval systems.

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

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

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

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

🏝️ Benefits

• 100% remote work.

• Equal employment opportunities without discrimination.

• Inclusive work environment.

• Diverse and dynamic, non-hierarchical work culture.