---
title: 'Staff Software Engineer - Snowhouse at Snowflake'
canonical: 'https://feeny.ai/job/staff-software-engineer-snowhouse-snowflake-menlo-park-ka5qxwv2pt4q'
type: 'job'
last_seen: '2026-09-18'
---

# Staff Software Engineer - Snowhouse at Snowflake

- **Company:** [Snowflake](https://feeny.ai/companies/snowflake)
- **Location:** Menlo Park, CA
- **Compensation:** $236k–$339k
- **Employment:** full-time
- **Posted:** 2026-08-27
- **Last confirmed live:** 2026-09-18
- **Apply:** https://jobs.ashbyhq.com/snowflake/68b45abb-f1d6-46b2-a30e-c551076e7e7e

## Job description

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: Lead cross-functional engineering projects from idea inception through implementation and production deployment across multiple quarters and teams. Develop a deep understanding of the underlying user and company needs.
- Cross-Functional Collaboration: Partner closely with product managers, senior ICs, data science teams, and business units to deliver end-to-end data platform capabilities.
- Platform Ownership: Own or co-own the reliability, observability, SLOs, capacity, and durable remediation goals for their problem space.

## Qualifications

- Experience: 12+ years of software development experience in distributed systems, with a strong focus on data warehouse or data infrastructure engineering.
- Cloud Infrastructure: Deep experience developing resilient, large-scale services in public cloud environments (AWS, Azure, or GCP).
- Technical Depth: Demonstrated proficiency in distributed systems architecture and database fundamentals, with a track record of solving complex system design challenges.
- Communication: Excellent technical communication and collaborative problem-solving skills across multidisciplinary teams.
- Bonus Skills: Familiarity with data or ML orchestration systems across diverse architectures.
- Education: BS, MS, or PhD in Computer Science or a related technical field (or equivalent practical experience).

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 is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: [careers.snowflake.com](http://careers.snowflake.com)

## About Snowflake

## Company Overview
- **One-liner**: Snowflake provides an AI Data Cloud platform that enables enterprises to store, analyze, and securely share their data across multiple clouds and geographies.
- **Entity Type**: Public (NYSE: SNOW)
- **Headquarters**: Bozeman, Montana, United States
- **Founded**: 2012
- **Founders**: Not explicitly listed in the provided search results (widely known co-founders include Benoit Dageville, Thierry Cruanes, Marcin Zukowski – not verified in these search results)

## Core Business
- **Primary Industry**: Enterprise software, cloud data platform
- **Target Customers**: B2B, including large enterprises (e.g., hundreds of the world’s largest companies), mid-market, and SMBs
- **Mission**: “To Mobilize the World’s Data” (Glassdoor) and “empower every enterprise to achieve its full potential through data and AI” (Snowflake Careers page)

## Products & Services
- **Snowflake AI Data Cloud**: A unified, multi-cloud platform that combines data warehousing, data lakes, data sharing, and AI/ML capabilities. Customers can discover, share, and analyze data while running analytic workloads across public clouds (AWS, Azure, GCP).
- **Snowflake Marketplace**: A marketplace for discovering and accessing third‑party data sets and applications.
- **Snowflake‑Powered Applications**: Platform for building and deploying data‑intensive applications.

## Market Standing
- **Valuation/Market Cap**: Not directly provided in search results (as a public company, market cap fluctuates and is available on financial websites).
- **Key Metric**: Annual Revenue – $1 to $5 billion (USD) per Glassdoor.
- **Notable Investors/Partners**: Not explicitly mentioned in the search results (historically backed by Sequoia Capital, Dragoneer, etc. – not verified here).
- **Growth Signals**:
  - Named #1 on the 2023 Fortune Future 50 List ([Fortune.com](https://fortune.com))
  - Listed as a U.S. Best Large Place to Work by BuiltIn in 2024
  - Recognized as one of the “20 Coolest Cloud Software Companies” by CRN in 2022 and 2024
  - Headcount of 5,001–10,000 employees with 30 global locations; actively hiring
  - Revenue range $1B–$5B indicates strong scale

## Competitive Advantages
- **Multi‑Cloud Flexibility**: Operates across AWS, Azure, and GCP, avoiding vendor lock‑in.
- **Unified Data Experience**: One platform for data sharing, analytics, and AI, reducing silos.
- **Separation of Compute and Storage**: Allows independent scaling and cost efficiency (not detailed in provided sources, but a known differentiator).
- **Strong Ecosystem**: Data marketplace and extensive partner network.

## Strategic Focus
- **AI & Data Innovation**: The company’s current emphasis is on making “enterprise AI easy, efficient, and trusted” and integrating AI capabilities into the Data Cloud.
- **Global Expansion**: Active hiring across 30 locations indicates continued geographic growth.
- **Customer‑Centric Development**: Focus on empowering enterprises to achieve “full potential through data and AI.”

## Why Work Here
- **Culture**: Described as “driven by innovation, low egos, high bars, and collaboration” (Snowflake Careers page). Glassdoor rating of 3.9/5 overall (78% approve CEO).
- **Work‑Life Balance**: Glassdoor rates Work/Life Balance at 3.7/5; many remote and hybrid roles available (see Indeed listings).
- **Benefits**: “Benefits & Beyond” program includes competitive compensation, equity, career advancement programs, and commitment to pay equality and veteran hiring.
- **Engineering Focus**: Hiring process includes 2–4 week timeline with technical interviews; the company values impactful, project‑based work for all roles, including interns.
- **Recognition**: Named a Best Large Place to Work (BuiltIn 2024) and future‑focused by Fortune, signaling strong employer brand.

## Sources
1. [Snowflake Careers Overview](https://careers.snowflake.com/us/en)
2. [Life at Snowflake](https://careers.snowflake.com/us/en/snowflake-life)
3. [Snowflake on Glassdoor](https://www.glassdoor.com/Overview/Working-at-Snowflake-EI_IE928471.11,20.htm)
4. [Snowflake Hiring Process](https://careers.snowflake.com/us/en/gethired)
5. [Snowflake on Indeed](https://www.indeed.com/cmp/Snowflake-7f4a7fba)
6. [Snowflake Careers Portal (Ashby)](https://jobs.ashbyhq.com/snowflake) – provided by user

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