Snowflake

Senior Software Engineer - Elastic Cloud Services

San Mateo, CA US
Azure GCP Kubernetes
Description

Build the future of data. Join the Snowflake team.

We’re at the forefront of the data revolution, committed to building the world’s greatest data and applications platform. Our ‘get it done’ culture allows everyone at Snowflake to have an equal opportunity to innovate on new ideas, create work with a lasting impact, and excel in a culture of collaboration.

 

Our product offering runs on multiple cloud providers including Amazon Web Services, Microsoft Azure and Google Cloud. Our infrastructure self-optimizes, provides high availability and data protection across cloud providers so our users can focus on using their data, not managing it. In our effort to enable our Data Cloud vision, we are actively hiring talented distributed systems engineers. This role is a unique opportunity to make a significant impact on our elastic, large scale, high-performance computing environment.

We are the Elastic Global Services team. We are responsible for building the highly available, scalable, multi-tenant  “Cloud Services” platform that underpin Snowflake services. Areas we are responsible for include, the autoscaling of VMs from Cloud providers, managing topologies of the VMs, cluster management, workload orchestration and many others. We are looking at expanding our team to handle the next big challenges for Snowflake customers.To learn more about the team’s tech stack, see our recent talk at ACM Symposium on Cloud Computing! https://acmsocc.org/2022/assets/slides/99.pdf

AS A SENIOR SOFTWARE ENGINEER AT SNOWFLAKE YOU WILL:

  • Solving real business needs at large scale by applying your software engineering and analytical problem solving skills.
  • Design and implement scalable distributed systems for our cloud services.
  • Analyze fault-tolerance and high availability issues, performance and scale challenges, and solve them.
  • Understand trade-offs between consistency, durability and costs to build solutions which can meet the demands of rapidly growing services.
  • Ensure operational readiness of the services and meet the commitments to our customers regarding availability and performance.

OUR IDEAL DISTRIBUTED SYSTEMS ENGINEER WILL HAVE:

  • 10+ years industry experience designing, building and supporting large scale infrastructure in production.
  • Experience building large scale distributed fault tolerant infrastructure.
  • Experience in container orchestration, cluster management, or autoscaling.
  • Excellent understanding of operating systems concepts including. multi-threading, memory management, networking and storage, performance and scale.
  • Solid understanding of the internals of Kubernetes, Mesos, OpenShift, or other container platforms.

WHY JOIN THE ENGINEERING TEAM AT SNOWFLAKE?

  • Build an industry-leading Cloud Data Platform.
  • Solve challenging technical problems related to security, parallel and distributed systems, programming, resource management, large-scale system maintenance, and more!
  • Work closely with our customers & partners, understand their use cases & needs, think strategically to seek the right problem to solve at the right time, and innovate with rigor. 
  • Join a world-class team of both industry veterans and rising stars.

Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.

Snowflake
Snowflake
Analytics Cloud Data Services Data Management Enterprise Software Software

0 applies

77 views

There are more than 22,000 engineering jobs:

Subscribe to membership and unlock all jobs

Engineering Jobs

39,000+ jobs from 4,300+ well-funded companies

Updated Daily

New jobs are added every day as companies post them

Refined Search

Use filters like skill, location, etc to narrow results

Become a member

Cancel anytime