Staff Engineer - Data Modeler

Role Description

The Senior Data Modeler will design and govern the data architecture for unstructured knowledge assets across the Knowledge Management (KM) ecosystem. This role bridges data engineering discipline with KM domain expertise, translating raw unstructured content into well-defined, discoverable, and secure data products within Databricks Unity Catalog.

This is a foundational hire for a newly formed KM Data Platform team supporting broader Knowledge and Research Systems strategy.

Key Responsibilities:

• Design logical and physical data models for unstructured and semi-structured content originating from KM pipelines.
• Define domain boundaries and ownership for data products.
• Establish metadata standards and tagging taxonomies to ensure consistent classification across knowledge sources.
• Assign and enforce security and sensitivity classifications on data products.
• Register, document, and maintain data products in Databricks Unity Catalog.
• Partner with data engineers building Databricks pipelines to ensure alignment with modeled domain structure.
• Collaborate with stakeholders to align data product design with downstream consumption needs.
• Support privacy and legal review processes by ensuring data products are classified and documented.
• Establish and document repeatable modeling standards/playbooks for future data products onboarding.

Qualifications

• Data Modeling (Strong), Databricks.
• 5+ years of experience in data modeling, data architecture, or information architecture.
• Direct experience in Knowledge Management, content management, or enterprise search domain.
• Hands-on experience with a modern data catalog; Databricks Unity Catalog experience preferred.
• Demonstrated ability to define data domains and data product boundaries.
• Practical knowledge of metadata management: tagging schemas, taxonomies, controlled vocabularies.
• Understanding of data security/sensitivity classification frameworks.
• Experience partnering with data engineering teams on ingestion and pipeline design.
• Strong written and verbal communication skills.

Requirements

• Good to have skills in BI Schema Design.
• Experience with enterprise knowledge platforms or AI-powered retrieval systems.
• Familiarity with Databricks Delta Lake, Delta Sharing, or Lakehouse Federation.
• Prior experience in professional services or a similar document/case-intensive knowledge environment.
• Exposure to Legal/Risk/Privacy review processes for data classification.
• Background in library science, information science, or applied ontology is a plus.

Success Metrics (First 6–12 Months)

• Domain model and metadata taxonomy defined and adopted for at least one major KM data product line.
• Data products registered and discoverable in Unity Catalog with correct security classifications applied.
• Documented, repeatable modeling standard for engineering and future modelers.
• Reduced turnaround time on privacy/legal classification reviews due to consistent metadata and tagging.

Company Description

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work on a scale across all devices and digital mediums, and our people exist everywhere in the world (18000 plus experts across 40 countries, to be exact). Our work culture is dynamic and non-hierarchical.