Databricks is looking to define, consolidate, and govern business metrics and semantic metadata for trusted access across Databricks products, focusing on query data modeling and driving technical direction for the UC Business Semantics team.
Requirements
- Built semantic layer/data modeling/metadata systems describing datasets, metrics, and data models to standardize business metrics.
- Worked on integration between semantic layers and BI platforms, ensuring tools like Tableau, Power BI, or other BI tools could query underlying models efficiently and consistently.
- Collaborated with product and BI teams to design business-friendly abstractions in SQL and metadata that map to organizational KPIs.
- Developed SQL language extensions (custom functions, new syntax, or dialect support) to improve analytical expressiveness for end users.
- Contributed to the query optimizer/planner of Spark SQL (or other query engine), implemented query rewrites and optimizations for semantic queries to execute efficiently in large-scale data engines.
- Experience connecting semantic models to agentic interfaces / LLM-based BI assistants, enabling natural language queries over structured data.
Responsibilities
- Provide technical guidance to multiple parallel projects led by other L6 engineers
- Define and execute the technical direction for UC Business Semantics
- Mentor and grow L6 engineers to L7, building team technical capacity
- Drive adoption of business semantics across Databricks and third-party tools
- Apply lessons from previous BI tools to implement better, more scalable solutions
- Work closely with the engineering leadership and peers to align on strategy, architecture, and roadmap
Other
- Strong track record of technical leadership and mentoring engineers
- Ability to drive adoption and influence product direction in a fast-paced environment
- Experience implementing scalable solutions and improving processes based on prior lessons
