Staff Engineer – Data Modeler
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Job Description
Staff Data Modeler designing secure unstructured-knowledge data products for Nagarro, a digital product engineering company. Governing metadata, domains, and Unity Catalog registration for KM platforms.
Responsibilities:
- Design logical and physical data models for unstructured and semi-structured content originating from Knowledge Management pipelines
- Define domain boundaries and ownership for reusable data products versus raw or intermediate assets
- Establish metadata standards and tagging taxonomies across knowledge sources
- Assign and enforce security and sensitivity classifications in line with governance, privacy, and legal/risk requirements
- Register, document, and maintain data products in Databricks Unity Catalog, including schemas, access grants, lineage, and catalog metadata
- Partner with data engineers to align ingestion, transformation, and storage patterns with the modeled domain structure
- Collaborate with Knowledge Products, Research Products, and Architecture/Data/Technology stakeholders on downstream consumption needs
- Support privacy and legal review processes through data-product classification and documentation
- Establish 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 first 6–12 months
Requirements:
- Strong data modeling skills
- Databricks experience
- 5+ years of experience in data modeling, data architecture, or information architecture
- Meaningful exposure to unstructured or semi-structured data
- Direct experience in or adjacent to Knowledge Management, content management, or enterprise search
- Hands-on experience with a modern data catalog; Databricks Unity Catalog strongly preferred
- Ability to define data domains and data product boundaries in a large, multi-stakeholder organization
- Practical 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 partnering with data engineering teams on ingestion and pipeline design
- Strong written and verbal communication skills
- Experience with enterprise knowledge platforms or AI-powered retrieval systems is a plus
- Familiarity with Databricks Delta Lake, Delta Sharing, or Lakehouse Federation is a plus
- Prior professional services, consulting, or document/case-intensive knowledge-environment experience is a plus
- Exposure to Legal/Risk/Privacy review processes is a plus
- Background in library science, information science, or applied ontology is a plus but not required
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