Staff Software Engineer - Snowhouse
Snowflake
- Pay
- $236k–$339k
- Workplace
- On-site
- Location
- US-CA-Menlo Park · Menlo Park · California · United States
- First seen
- 6 days ago
- Last seen
- 4 hours ago
- Board
- Ashby
Summary
At Snowflake, we are powering the era of the agentic enterprise.
Posting
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. Staff Software Engineer - Snowhouse Foundation About the Team The Snowhouse Foundation team builds our globally distributed data warehouse, managing vast petabyte-scale datasets that are continuously ingested, processed, and replicated across all Snowflake environments and external data sources. Snowhouse powers Snowflake's core business, engineering, and data science operations while delivering critical customer visibility into global account activities, usage, and resource consumption. The team drives critical investments in core data processing infrastructure, high-performance data export/ingestion, optimized data layout and compliance, and Snowflake's system database and applications. A successful candidate will: - Deeply understand the inner workings of Snowflake and the needs of our users, exhibiting a healthy curiosity for use cases and needs that will inform future technical strategy, anticipating needs rather than reacting to them. - Be highly productive by leveraging AI-assisted engineering, empowering and creating opportunities for others, and effectively leading at scale. - Show a natural inclination to partner across teams to deliver improvements on cross-team concerns such as reliability and efficiency. Responsibilities - Technical Leadership: Provide hands-on guidance and code reviews, develop other engineers and raise the quality bar, establish engineering best practices across the team and contribute to the team strategy and future of the platform. - Technical Execution: Design and implement highly available distributed platforms, pipelines, and data infrastructure components to scale global data processing. Solve hard problems, use AI-assisted engineering responsibly to improve velocity and quality. - Problem-space Ownership: Lea