About the job
P-150
At Databricks, we are dedicated to empowering data teams to tackle some of the world's most challenging problems, ranging from security threat detection to the development of cancer treatments. We achieve this by creating and managing the leading data and AI infrastructure platform, allowing our clients to concentrate on the high-value challenges central to their missions.
Founded in 2013 by the original creators of Apache Spark™, Databricks has evolved from a modest office in Berkeley, California, to a global enterprise with over 1000 employees. Our platform is trusted by thousands of organizations, from startups to Fortune 100 companies, establishing us as one of the fastest-growing SaaS firms worldwide.
Our engineering teams design and develop highly technical products that meet significant real-world needs. We continually push the limits of data and AI technology while maintaining the resilience, security, and scalability essential for our customers' success on our platform.
We operate one of the largest-scale software platforms, comprising millions of virtual machines that generate terabytes of logs and process exabytes of data daily. Given our scale, we frequently encounter cloud hardware, network, and operating system faults, and our software must effectively shield our customers from any disruptions.
As a Software Engineer focused on backend development, you will collaborate closely with your team and product management to prioritize, design, implement, test, and operate microservices for the Databricks platform and products. This role includes writing software in Scala/Java, building data pipelines using Apache Spark™ and Apache Kafka, integrating with third-party applications, and interacting with cloud APIs such as AWS, Azure, CloudFormation, and Terraform.
Below are examples of teams you can join:
Data Science and Machine Learning Infrastructure: Develop services and infrastructure that bridge the gap between machine learning and distributed systems. Our technology supports flagship collaborative workspaces, notebooks, IDE integrations, and project management tools. We also facilitate large-scale machine learning through environment management, distributed training, and lifecycle management via MLflow.
Compute Fabric: Construct the resource management infrastructure that supports all big data and machine learning workloads on the Databricks platform in a robust, flexible, secure, and cloud-agnostic manner. This software oversees millions of virtual machines.

