Snowflake
Engineering Manager - Cloud Efficiency
- Employment type
- Full-time
- Workplace type
- Hybrid
- Location
- US-WA-Bellevue
- Published
- Sep 18, 2026
- Last checked
- Oct 26, 2026
About this role
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
Engineering Manager, Cloud Efficiency
Snowflake runs large scale cloud infrastructure to deliver its own service — production and internal deployments, Kubernetes fleets, CI/CD, etc. Our cloud spend is in billions of dollars per year. We are looking for an experienced Engineering Manager to lead the Cloud Efficiency engineering team. In this role, you will own the technical vision and execution for building a unified, self-serve cloud efficiency platform along with AI skills and agents that makes resource usage and spend attributable and governable while driving insights and optimization of our cloud spend.
AS AN ENGINEERING MANAGER IN CLOUD EFFICIENCY, YOU WILL:
- Lead and grow our talented team of software engineers, fostering a culture of technical excellence, ownership, and continuous learning.
- Drive the roadmap for Cloud Efficiency — translating company-level spend objectives into engineering systems: authoritative cost data, resource ownership registry, attribution pipelines, cost and unit economics modeling, observability, governance policies, and optimization workflows — in partnership with Product, Engineering, Finance, and Data Science.
- Set technical strategy for backend systems, data pipelines, and APIs that measure, attribute and surface cost and usage insights at massive scale.