Job location
Mountain View, United States of America
Tech stack
Java
Amazon Web Services (AWS)
Azure
C++
Cloud Computing
Distributed Systems
Service-Oriented Architecture
Google Cloud Platform
Kubernetes
Information Technology
Docker
Requirements
Do you have experience in Technology infrastructure engineering?, Do you have a Bachelor's degree?, * BS (or higher) in Computer Science or related field
- 5+ years of experience designing and building large-scale distributed systems
- Strong proficiency in one or more languages such as Java, Scala, Go, or C++
- Experience with service-oriented architectures and large scale distributed systems
- Familiarity with cloud platforms (AWS, Azure, GCP) and container/orchestration technologies (Kubernetes, Docker)
- Track record of shipping infrastructure that supports mission-critical workloads at scale
Benefits & conditions
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.
Local Pay Range
$164,200-$205,200 USD, At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.
About the company
At Databricks, we are passionate about helping data teams solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers - and customer obsessed - we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.
At Databricks, the Compute Infrastructure organization builds and operates the foundation that runs all Data, AI and stateful workloads across all major clouds. Our platform launches tens of millions of VMs per day, operates thousands of Kubernetes clusters, and must deliver extreme elasticity, reliability and cost efficiency.
As a Senior Software Engineer on the Compute Infra team, you will design and build the systems that power Databricks' compute infrastructure to enable engineers to quickly launch and scale world-class products.
The impact you will have:
* Develop the compute abstractions that provide powerful capabilities for all Databricks workloads, enabling engineers to build world-class products with high velocity and best-in-class performance
* Design the workload orchestration and scheduling systems that orchestrates all types of workloads (serving, batch, stateful, GPU) with high performance and efficiency
* Scale the fleet management systems that launch and configure millions of VMs every day across cloud providers
* Raise the technical and operational bar through strong design practices, testing, and a culture of engineering excellence and platform mindset.
* Lead cross-team initiatives that span product and infrastructure surface areas., Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.