Job Description

The problem

Organizations with multiple locations run different systems (EHR, HR, finance). Each dumps raw data in different formats and schemas. We want to unify this into a central semantic model – without forcing locations to change their systems.

What we’re trying to achieve
  • Automatically understand what’s in a raw database schema
  • Detect when tables across different sources represent the same entity
  • Merge and map local data to a central ontology
  • Make this process automated with human‑in‑the‑loop supervision
One route we’re exploring

Cube‑based semantic layer(s) with agent‑assisted schema generation and entity matching. But we’re open to other approaches: dbt, custom tooling, graph‑based solutions, etc.

Your profile
  • 5+ years data engineering
  • Deep experience with data modeling and schema design
  • Worked with multi‑source data integration challenges
  • ...

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