- Design and build AI-ready Databricks data products with business semantics, KPIs, hierarchies, and glossary alignment.
- Implement semantic layers and governed datasets for BI and natural-language querying.
- Deploy and operate Databricks Genie spaces with Unity Catalog, tuning for accuracy, adoption, and business relevance.
- Build RAG pipelines and conversational analytics applications grounded in governed enterprise data.
- Develop Streamlit or Databricks Apps that let business users query data without writing SQL.
- Engineer ETL/ELT pipelines using dbt, Airflow, and PySpark.
- Implement governance controls including access security, masking, lineage, auditability, catalog, and metadata management.
- Optimize data platform and AI costs and performance, including warehouse sizing, cluster tuning, query optimization, token usage, caching, and model routing.
- Partner with Finance stakeholders to translate domain requirements into semantic models and governed data products.
PythonSQLAirflow+3 more