Sr. Staff Software Engineer - Data Platform
Databricks - Mountain View, California; San Francisco, California
Posted Oct 10, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Deadline
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Where they hire
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About this role
Sr. Staff Software Engineer - Data Platform Mountain View, California; San Francisco, California RDQ126R106 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 Sr. Staff Software Engineer you will be part of the executive leadership team on the Data Platform org. You will leverage bleeding-edge AI developer tools and techniques to help build the Data Intelligence Platform that will allow us to automate decision-making across Databricks. You will achieve this in collaboration with prominent Tech Leads, 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
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