Data Engineer – Semantic Data Integration Pulsr

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...