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 and improving the developer experience.
- Improve reliability and cost-efficiency by optimizing log retention, indexing, and query performance to reduce operational overhead.
- Mentor and uplevel engineers, fostering a culture of technical excellence within the team and broader observability community.
What we look for:
- BS (or higher) in Computer Science, or a related field.
- 7+ years of production-level experience in one of: Scala, Rust, Go, Python, Java, C++, or similar languages.
- Deep experience in software development, in large-scale distributed systems.
- Experience driving complex projects involving multiple teams and stakeholders.
- Familiarity with log collection, health monitoring, and observability tools.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
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
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
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.
Applicant Privacy Notice
Skills Required
- 7+ years of production-level experience in one of: Scala, Rust, Go, Python, Java, C++, or similar languages.
- Deep experience in software development, in large-scale distributed systems.
- Experience driving complex projects involving multiple teams and stakeholders.
- Familiarity with log collection, health monitoring, and observability tools.
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Equity Value & Accessibility — Equity grants are a meaningful part of offers, and periodic tender opportunities and secondary options have made private equity more tangible for many employees. This perceived upside contributes to strong total-compensation sentiment in key roles.
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Healthcare Strength — Comprehensive medical, dental, and vision coverage is paired with mental‑health resources and wellness reimbursements, indicating a robust health package. Multiple summaries highlight broad coverage that employees can practically use.
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Leave & Time Off Breadth — Generous PTO, paid holidays/sick time, and fully paid parental leave are frequently described, with hybrid/remote flexibility common in the U.S. These policies expand time‑off accessibility across different life stages.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
