AI Data Enablement Engineer

Our Client's Digital Finance IT is building an AI-enablement layer on top of our enterprise data platform to enable business users across Finance to interact with governed data in natural language. We're hiring a Data Enablement Engineer to design, build, and operate the trusted datasets, semantic models, and embedded AI experiences that make this possible.

This is a data platform engineering role, not a data science or model-building role. You will spend your time engineering the data foundation that makes AI reliable — semantic layers, governed data products, and embedded natural-language analytics — not training models.

What You'll Do

• Design and build AI-ready data products on Snowflake and/or Databricks — trusted datasets with well-defined business semantics, KPIs, hierarchies, and business glossary alignment
• Implement semantic layers and governed datasets that support both traditional BI consumption and natural-language querying by business users
• Deploy and operate Snowflake Cortex capabilities (Cortex Analyst, Cortex Search, Cortex Agents, Cortex LLM Functions) and/or Databricks Genie spaces with Unity Catalog, tuning them for accuracy, adoption, and business relevance
• Build RAG pipelines and conversational analytics applications grounded in governed enterprise data — including Streamlit