Staff Engineer – Data Engineer

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

📋 Description

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

• Define the boundaries and ownership of data products within specific domains.

• Establish standards for metadata and tagging taxonomies across various knowledge resources.

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

• Register, document, and maintain data products in the Databricks Unity Catalog, including schemas, access permissions, lineage, and catalog-level metadata.

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

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

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

• Develop and document repeatable modeling standards and playbooks.

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

⛳️ Requirements

• Minimum of 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; familiarity with Databricks Unity Catalog is highly preferred.

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

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

• Understanding of data security and sensitivity classification frameworks along with access control in a lakehouse environment.

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

• Excellent written and verbal communication skills.

• Preferred experience with enterprise knowledge platforms or AI-driven retrieval systems.

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

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

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

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

• Must possess strong Data Modeling and Databricks skills.

🏝️ Benefits

• Opportunity for remote work.