About the job
P-940
This position is open to our offices in both Seattle and Bellevue.
At Databricks, we are dedicated to empowering data teams to tackle the world's most pressing challenges, from detecting security threats to innovating in cancer drug development. By constructing and managing the globe's premier data and AI infrastructure platform, we enable our clients to concentrate on the critical challenges central to their missions.
Founded in 2013 by the original architects of Apache Spark™, Databricks has expanded from a modest office in Berkeley, California to a global powerhouse with over 1,000 employees. We are proud to be one of the fastest-growing SaaS companies, trusted by thousands of organizations ranging from startups to Fortune 100 companies with their most vital workloads.
Our engineering teams develop highly technical products that address significant global needs. We continually push the limits of data and AI technology, while ensuring the resilience, security, and scalability essential for our customers' success on our platform.
We operate one of the largest-scale software platforms, comprised of millions of virtual machines that generate terabytes of logs and process exabytes of data daily. Given our scale, we routinely encounter cloud hardware, network, and operating system faults, and our software is engineered to seamlessly shield customers from these issues.
As a backend-focused software engineer, you will collaborate closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and products. This role involves writing software in Scala/Java, building data pipelines (Apache Spark™, Apache Kafka), integrating with third-party applications, and engaging with cloud APIs (AWS, Azure, CloudFormation, Terraform).
Join one of our dynamic teams, such as:
Data Science and Machine Learning Infrastructure: Develop services and infrastructure at the nexus of machine learning and distributed systems. Our technology powers the flagship collaborative workspace, notebooks, IDE integrations, and project management tools. We facilitate machine learning at scale with tools for environment management, distributed training, and managing the machine learning lifecycle through MLflow.
Compute Fabric: Create the resource management infrastructure that supports all big data and machine learning workloads on the Databricks platform in a robust, flexible, and secure manner.

