AI Data Enablement Engineer

About the role

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 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 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 or Databricks Apps that let business users query…
• Engineer robust ETL/ELT pipelines (dbt, Airflow, PySpark) that produce and maintain the trusted data these AI experiences depend on

What you need

• 5–9 yrs of experience
• SQL
• Python
• Databricks
• dbt
• Airflow
• Spark
• Any graduate

Good to have

• Machine learning
• LLMs
• Computer vision
• NLP
• CRM
• SAP