At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions.
Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world.
Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform.
As a software engineer with a backend focus, you will work closely with your team and product management to prioritize, design, implement, test, and operate micro-services for the Databricks platform and product. This implies, among others, 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).
Below Are Some Example Teams You Can Join
Data Science and Machine Learning Infrastructure:
Build services and infrastructure at the intersection of machine learning and distributed systems.
Compute Fabric:
Build the resource management infrastructure powering all the big data and machine learning workloads on the Databricks platform.
Data Plane Storage:
Deliver reliable and high performance services and client libraries for storing and accessing large amounts of data on cloud storage backends.
Enterprise Platform:
Offer a simple and powerful experience for onboarding and managing all of their data teams across thousands of users on the Databricks platform.
Observability:
Provide a world class platform for Databricks engineers to comprehensively observe and introspect their applications and services.
Service Platform:
Build high-quality services and manage the services in all environments in a unified way.
Core Infra:
Build the core infrastructure that powers Databricks, making it available across all geographic regions and Cloud providers.
Competencies
- BS/MS/PhD in Computer Science, or a related field
- 2+ years of production level experience in one of: Java, Scala, C++, or similar language.
- Comfortable working towards a multi-year vision with incremental deliverables.
- Experience in architecting, developing, deploying, and operating large scale distributed systems.
- Experience working on a SaaS platform or with Service-Oriented Architectures.
- Good knowledge of SQL.
- Experience with software security and systems that handle sensitive data.
- Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes.
Benefits
- Comprehensive health coverage including medical, dental, and vision
- 401(k) Plan
- Equity awards
- Flexible time off
- Paid parental leave
- Family Planning
- Gym reimbursement
- Annual personal development fund
- Employee Assistance Program (EAP)
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base salary range for non-commissionable roles or on-target earnings for commissionable roles.
Local Pay Range: $192,000—$260,000 USD
About Databricks
Databricks is the data and AI company. More than 9,000 organizations worldwide rely on the Databricks Lakehouse Platform to unify their data, analytics and AI.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel.
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.
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