📋 Description

• Define schema, taxonomy, and graph modeling for knowledge domains.
• Design document structures and how facts evolve over time.
• Build ingestion/ETL pipelines from SharePoint and Microsoft stack.
• Keep knowledge graph in sync as sources change.
• Advise on backend approach (Supabase/Postgres) and ensure content quality.
• Establish data quality, lineage, and governance across pipelines.

🎯 Requirements

• Bachelor’s Degree in CS or related field.
• 5+ years in data engineering/architecture roles.
• Deep data modeling across relational and graph; Neo4j and Postgres/Supabase at scale.
• Strong ETL/data pipeline engineering in Python; large-scale ingestion.
• Experience with enterprise content ecosystems: SharePoint, Power Platform/Power Automate.
• Knowledge representation, taxonomies/ontologies, and versioned/temporal data.

🎁 Benefits

• Knowledgeable, global team; opportunities for impact in data-driven architecture.