Staff Engineer – Data Modeler

This is a fully remote position, open to applicants in United States.

📋 Description

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

• Determine the boundaries and ownership of reusable data products in comparison to raw or intermediate assets.

• Set metadata standards and tagging taxonomies across various knowledge sources.

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

• Register, document, and manage data products within Databricks Unity Catalog, including schemas, access grants, lineage, and catalog metadata.

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

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

• Assist in privacy and legal review processes through data product classification and documentation.

• Develop repeatable modeling standards and playbooks for onboarding future data products.

• Deliver domain models, metadata taxonomies, registered Unity Catalog data products, and repeatable modeling standards within the initial 6–12 months.

⛳️ Requirements

• Proficient data modeling skills.

• Experience with Databricks.

• Over 5 years of experience in data modeling, data architecture, or information architecture.

• 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 highly preferred.

• Ability to define data domains and product boundaries within a large, multi-stakeholder organization.

• Hands-on knowledge of metadata management, tagging schemas, taxonomies, controlled vocabularies, or ontology design.

• Understanding of data security/sensitivity classification frameworks and access control in a Lakehouse environment.

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

• Excellent written and verbal communication skills.

• Experience with enterprise knowledge platforms or AI-powered retrieval systems is an advantage.

• Familiarity with Databricks Delta Lake, Delta Sharing, or Lakehouse Federation is a plus.

• Prior experience in professional services, consulting, or document/case-intensive knowledge environments is beneficial.

• Exposure to Legal/Risk/Privacy review processes is advantageous.

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

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible working hours and remote work options.

• Opportunities for professional development and training.

• Supportive work environment focused on innovation and collaboration.