Staff Engineer, Data 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 Bain's Knowledge Management ecosystem.

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

• Define the boundaries and ownership for data products.

• Establish standards for metadata and tagging taxonomies.

• Assign and enforce classifications for security and sensitivity on data products.

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

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

• Work in partnership with Knowledge Products, Research Products, and Architecture/Data/Technology stakeholders regarding downstream consumption requirements.

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

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

⛳️ Requirements

• Over 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 adjacent to Knowledge Management, content management, or the enterprise search domain.

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

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

• Working knowledge of metadata management, including tagging schemas, taxonomies, controlled vocabularies, or ontology design.

• Understanding of data security and sensitivity classification frameworks, as well as access control within a lakehouse environment.

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

• Excellent written and verbal communication skills; ability to articulate technical modeling decisions in a manner that is understandable to business stakeholders.

• Preferred: experience with Glean, SharePoint, ServiceNow, or AI-driven retrieval systems.

• Preferred: familiarity with Databricks Delta Lake, Delta Sharing, or Lakehouse Federation.

• Preferred: prior experience in professional services, consulting, or a document/case-intensive knowledge environment.

• Preferred: exposure to Legal/Risk/Privacy review processes.

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

🏝️ Benefits

• Employees have the option to work remotely.