Software Engineer, Enterprise Team
Snowflake
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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world’s leading data platforms.
The Team:
We are hiring a Software Engineer, Enterprise for our Engineering team at Observe by Snowflake. As part of the Enterprise Engineering team at Observe by Snowflake, you’ll build and scale core features, APIs, and business logic powering a high-performance observability platform. You’ll develop reliable, production-grade systems designed to handle massive volumes of telemetry for enterprise customers. Working at the intersection of data, infrastructure, and user experience, you’ll help deliver solutions that enable fast, actionable insights at scale. This is an opportunity to own impactful systems that directly support the reliability and performance of some of the world’s largest organizations.In this role your will:
- Design, build, and own core features, APIs, and business logic powering a high-performance observability platform for enterprise customers
- Take end-to-end ownership from technical scoping and architecture through deployment, ensuring systems meet enterprise reliability and performance standards
- Collaborate with product, infrastructure, and data teams to deliver solutions that enable fast, actionable insights for engineering teams worldwide
- Partner with SREs and customer-facing teams to diagnose and resolve production issues, applying AI-assisted workflows to accelerate root-cause analysis
- Contribute to high engineering standards through thoughtful code review, mentorship, and architectural influence
Qualifications:
- 2 - 5 years of professional software engineering experience with a focus on backend application systems or distributed platforms
- Demonstrated experience designing and shipping production systems at scale, handling high throughput, low latency, and enterprise reliability requirements
- Strong proficiency in one or more server-side languages such as Go, Java, Scala, Python, or similar
- Ability to work independently and take ownership of complex technical problems from scoping through delivery, without waiting to be directed
- Experience collaborating across engineering, product, and infrastructure teams in a fast-moving, high-ownership environment
- Strong analytical thinking and structured problem-solving skills with a track record of shipping impactful, customer-facing work
- A BS/MS in Computer Science, Engineering, or equivalent experience
Bonus Points:
- Experience with observability platforms, telemetry pipelines, or distributed tracing and logging systems (e.g., OpenTelemetry, Prometheus, Jaeger)
- Experience building or contributing to AI-assisted developer tools or LLM-integrated workflows
- Background in SRE practices, incident response automation, or root-cause analysis tooling
- Open-source contributions to observability, data infrastructure, or developer productivity projects
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