Staff Software Engineer — Engineering Systems, Continuous Integration
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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.
About SnowflakeSnowflake is building the AI Data Cloud, enabling organizations around the world to mobilize data and develop applications at global scale. The Engineering Systems organization builds the infrastructure, tools, and platforms that help Snowflake engineers develop, test, and deliver high-quality software efficiently.
The Continuous Integration team is responsible for the systems that power builds, tests, validation, and developer workflows across Snowflake’s engineering organization. As a Staff Software Engineer on this team, you will help define the technical direction of critical CI infrastructure used by thousands of engineers across a rapidly growing, multi-cloud codebase.
As a Staff Software Engineer, You Will- Own the technical direction and architecture of large-scale Continuous Integration services and infrastructure.
- Design, build, and operate distributed systems that support reliable, performant, and secure software delivery.
- Lead the development of CI capabilities that improve build reliability, test execution, developer productivity, and release velocity.
- Partner with engineering leadership, product managers, and teams across Snowflake to define quarterly and long-term technical roadmaps.
- Drive architectural decisions across build systems, test orchestration, resource scheduling, workflow execution, and developer tooling.
- Identify systemic bottlenecks in the software delivery lifecycle and develop solutions that improve engineering efficiency at scale.
- Establish high standards for design, code quality, testing, observability, reliability, and operational readiness.
- Mentor engineers through design reviews, code reviews, technical guidance, and collaborative problem-solving.
- Lead complex projects involving multiple teams and cross-functional dependencies.
- Participate in incident response, root-cause analysis, and long-term reliability improvements.
- Evaluate emerging technologies and industry practices to keep Snowflake’s developer platform scalable and effective.
Our Ideal Staff Software Engineer Will Have- 7+ years of industry experience designing and building production software systems.
- A track record of technical leadership across complex, multi-team engineering initiatives.
- Deep experience designing and operating distributed systems at scale.
- Experience building or significantly evolving enterprise-grade Continuous Integration or Continuous Delivery systems.
- Strong computer science fundamentals, including data structures, algorithms, distributed systems, and systems design.
- Proficiency in one or more programming languages such as Java, C++, Python, or Go.
- Experience making architectural decisions involving scalability, reliability, performance, security, and maintainability.
- A strong understanding of developer productivity and the software development lifecycle.
- Excellent problem-solving skills and sound technical judgment.
- Strong written and verbal communication skills, with the ability to explain complex technical concepts clearly.
- A collaborative mindset and a demonstrated ability to mentor and influence engineers across teams.
Preferred Qualifications- Experience with CI/CD and build systems such as Jenkins, GitHub Actions,...
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About Snowflake
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Cloud data platform for storing, analyzing and sharing data and building AI applications.
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