Staff Software Engineer, Observability

• You will build the next generation of observability platforms that support billions of active time series and process petabytes of logs daily.
• You will manage infrastructure across nearly a hundred cloud regions, enabling all Databricks engineers and customers to monitor the reliability of our product.
• You will develop advanced workflows that accelerate incident diagnosis for Bricksters, allowing engineers to quickly derive insights from logs and metrics. You will leverage powerful capabilities of Databricks' own data intelligence platform to push the boundaries of troubleshooting practices in the industry.
• You will uplevel monitoring and reliability practices across Databricks engineering, developing opinionated tools that set common standards for managing structured logs, metrics, alerts, dashboards, and oncall rotations.
• Mentor and uplevel engineers, fostering a culture of technical excellence within the team and broader observability community.

Do you have experience in Tooling?, Do you have a Bachelor's degree?, + BS (or higher) in Computer Science, or a related field.

• 7+ years of production-level experience in one of: Go, Python, Java, Scala, Rust, C++, or similar languages.
• Experience in software development, in large-scale distributed systems.
• Experience driving large projects involving multiple teams
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.
• Familiarity with observability infrastructure, monitoring patterns, and reliability practices.

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.

Zone 1 Pay Range $190,000-$261,250 USD, At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.

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. Our engineering teams build technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the security and scale that is important to making customers successful on our platform. We develop and operate one of the largest-scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a software engineer in the Observability team, you will develop observability solutions that provide insights into the health and performance of our products and infrastructure., Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.