Staff Software Engineer - Data Platform

About the role

P-375

At Databricks, we are passionate about enabling data teams to 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 tackle 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.

As a Staff Software Engineer working on the Data Platform team, you will leverage bleeding-edge AI developer tools and techniques to help build the Data Intelligence Platform for Databricks that will allow us to automate decision-making across the entire company. You will achieve this in collaboration with Databricks Product Teams, Data Science, and many more. You will define the future of a variety of tools spanning logging, orchestration, data transformation, metric store, governance platforms, and data consumption layers, just to name a few.

The impact you will have

• Design and run the cross-company Data Intelligence Platform, which contains every business and product metric used to run Databricks. You’ll play a key role in developing the right balance of data protection and ease of shareability for the Data Intelligence Platform as we transition to a public company.

• Develop tooling and infrastructure to efficiently manage and run Databricks on Databricks at scale, across multiple clouds, geographies, and deployment types. This includes CI/CD processes, test frameworks for pipelines and data quality, and infrastructure-as-code tooling.

• Partner with our engineering teams to provide leadership in developing the long-term vision and requirements for the Databricks product.

• Build reliable data pipelines and solve data problems using Databricks, our partner’s products, and other OSS tools. Provide early feedback on the design and operations of these products.

• Represent Databricks at academic and industrial conferences & events.

What we look for

• BS/MS/PhD in Computer Science or related majors, or equivalent experience.

• 10+ years of industry experience building and operating large-scale distributed systems.

• 4+ years of experience providing technical leadership on planet-scale production data systems

• Experience leading architecture efforts for performance-sensitive systems (e.g., latency-critical services, multi-tenant platforms, large-scale indexing pipelines).

• Strong communication skills and the ability to operate effectively in fast-paced, cross-functional environments.

• A strategic mindset with the ability to align engineering execution with longer-term product and company goals.

• Passion for mentoring and developing other engineers.

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.