The impact you'll have is significant, as our backend teams cover a diverse range of domains, from core compute fabric resource management to service platforms and machine learning infrastructure.

For example, you might work on challenges such as:

• Supporting Databricks' growth by building foundational infrastructure platforms that enable seamless operation across numerous geographic regions and cloud providers.

• Implementing cloud-agnostic infrastructure abstractions to help Databricks engineers more efficiently manage and operate their services.

• Developing tools and processes that drive engineering efficiency at Databricks.

We enhance the developer experience for Databricks engineers across various areas, including programming languages, linters, static analysis, IDEs, remote development environments, automated release pipelines, and test automation frameworks.

Our current focus is on optimizing the Rust development experience across the organization.

To be successful in this role, you will need:

• 8+ years of professional software development experience.

• A bachelor's degree or higher in Computer Science, a related field, or equivalent experience.

• Proficiency in one or more backend languages such as Java, Scala, or Go.

• Hands-on experience in developing and operating large-scale, critical distributed backend systems.

• Demonstrated leadership throughout all project phases, from inception and design to implementation and operations, with a strong ability to drive architectural decisions and guide teams through complex challenges.

• Experience mentoring engineers, influencing best practices, and fostering a collaborative engineering environment.

• Self-driven and passionate with a strong focus on delivering impact through team collaboration.

• Strong written and verbal communication skills to drive alignment across teams, and contribute to both technical documentation and strategic decisions.

• Experience with infrastructure systems, security, and sensitive data, as well as familiarity with Kubernetes or cloud platforms like AWS, Azure, or GCP.

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