📋 Description

• Define the schema, taxonomy, and graph modeling for knowledge domains.
• Design document and version structures, including temporal replay for evolving facts.
• Build ingestion/ETL pipelines from enterprise content sources (SharePoint, Microsoft stack).
• Keep knowledge graph in sync as source documents change frequently.
• Advise on backend architecture (Supabase/Postgres) and validate ingested content quality with QA.
• Establish data quality, lineage, and governance across pipelines.

🎯 Requirements

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

🎁 Benefits