Staff Software Engineer - Backend

Databricks Databricks · Data AI · San Francisco, CA · Engineering - Pipeline

Databricks is seeking a Staff Software Engineer - Backend to work on their data and AI infrastructure platform. The role involves designing, implementing, testing, and operating micro-services for the platform, focusing on backend development with languages like Scala/Java, data pipelines, and cloud integrations. The role is not directly building AI models but supporting the infrastructure for data and AI teams.

What you'd actually do

  1. work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product
  2. writing software in Scala/Java, building data pipelines (Apache Spark, Apache Kafka), integrating with third-party applications, and interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform)
  3. Build services and infrastructure at the intersection of machine learning and distributed systems.
  4. Build the resource management infrastructure powering all the big data and machine learning workloads on the Databricks platform in a robust, flexible, secure, and cloud-agnostic way.
  5. Provide a world class platform for Databricks engineers to comprehensively observe and introspect their applications and services.

Skills

Required

  • BS/MS/PhD in Computer Science, or a related field
  • 10+ years of production level experience in one of: Java, Scala, C++, or similar language.
  • architecting, developing, deploying, and operating large scale distributed systems
  • working on a SaaS platform or with Service-Oriented Architectures
  • cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes

Nice to have

  • building data pipelines (Apache Spark, Apache Kafka)
  • integrating with third-party applications
  • interacting with cloud APIs (AWS, Azure, CloudFormation, Terraform)
  • software security
  • systems that handle sensitive data
  • Good knowledge of SQL

What the JD emphasized

  • large scale distributed systems
  • SaaS platform
  • cloud technologies