Sr. Staff Software Engineer Unity Catalog Business Semantics

At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

The Unity Catalog Business Semantics team is responsible for defining, consolidating, and governing business metrics and semantic metadata for trusted access across Databricks products. The team collaborates closely with other engineers and contributors to ensure that business semantics are accurate, consistent, and easy to consume.

We are seeking a Senior Staff Engineer (L7) to take technical leadership of the UC Business Semantics team. This individual will focus on query data modeling, driving technical direction, mentoring engineers, and influencing adoption both within Databricks products and in the wider BI ecosystem.

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

What We Look For

• 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.


• 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