Role at a glance
- Salary
- $190K – $261.3K/yr
- Location
- Mountain View, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 7+ years of production-level experience in one of: Go, Python, Java, Scala, Rust, C++, or similar languages.
- Education
- BS (or higher) in Computer Science, or a related field.
Spotted an issue?
We’ll check it against the original posting.
Role Summary
The Observability team develops observability solutions for the health and performance of Databricks products and infrastructure. The role focuses on building large-scale platforms and workflows that help engineers monitor reliability and diagnose incidents across Databricks engineering.
What You'll Do
- Build observability platforms that support billions of active time series and process petabytes of logs daily.
- Manage infrastructure across nearly a hundred cloud regions.
- Develop workflows that accelerate incident diagnosis using logs and metrics.
- Develop tools and standards for structured logs, metrics, alerts, dashboards, and oncall rotations.
- Mentor and uplevel engineers within the team and broader observability community.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
BS (or higher) in Computer Science or a related field; 7+ years of production-level experience in 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 such as AWS, Azure, GCP, Docker, or Kubernetes; familiarity with observability infrastructure, monitoring patterns, and reliability practices.
Required
- 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.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
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.
The impact you'll have:
- 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.
What we look for:
-
- 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. 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.
About the company
Databricks
Large Enterprise
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.