Staff Software Engineer, Metrics and Logging
Databricks - Mountain View, California
Posted Nov 19, 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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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Staff Software Engineer, Metrics and Logging Mountain View, California RDQ426R299 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. The Logging Platform team plays a critical role in building scalable and efficient logging solutions that power observability across all Databricks services. As a Staff Software Engineer, you will drive the next generation of our logging infrastructure, enabling engineers across the company to gain deep insights into system behavior, troubleshoot issues efficiently, and optimize performance at scale. The impact you'll have: - Build the future of logging at Databricks by designing and scaling our next-generation logging platform that processes petabytes of logs daily. - Develop and optimize log delivery pipelines to support low-latency, high-throughput log ingestion and querying, ensuring seamless observability across all Databricks services. - Enhance log accessibility and usability, developing tools that enable engineers to efficiently search, analyze, and derive insights from logs. - Collaborate with teams across Databricks to define best practices for structured logging, standardizing formats
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