Senior Software Engineer - Observe by Snowflake, Indexing and Query Execution
Indexed description
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 Role
You'll be our dedicated expert in query execution and query performance. That means owning the query execution service end-to-end: working on caching strategies, incremental execution, query rewrites, and other optimizations that directly affect the speed and cost of running Observe at scale. You'll also be the go-to resource when query latency issues arise during customer evaluations and new deal cycles, diagnosing root causes quickly and driving lasting fixes.
This is a high-ownership, high-impact role. You'll partner closely with Snowflake's engineering and product teams to surface gaps and advocate for platform improvements that benefit Observe, and work across our backend systems to close performance gaps before they become customer problems.
You'll excel here if you're equally comfortable doing rigorous performance analysis at scale (across millions of queries) and diving into the mechanics of a single slow query to find the fix.
What You'll Do
- Own and evolve the query execution service, including query caching, incremental execution, query rewrites, and decomposition strategies
- Systematically analyze large volumes of user and system-generated queries to identify performance bottlenecks and drive improvements
- Investigate and resolve customer-reported query latency issues, including acting as a first responder during new deal evaluations where query performance is under scrutiny
- Work on automated tuning of system parameters to reduce query execution times and costs
- Partner with Snowflake engineering and product teams to advocate for platform improvements, communicate requirements clearly, and drive resolutions
- Propose, scope, and deliver improvements to the query execution pipeline with attention to both short-term fixes and long-term architecture
- 5+ years of industry experience building distributed systems
- Hands-on experience working below the query interface, on the execution machinery itself (e.g., query planning, caching, rewrite rules, execution engines)
- Proven ability to diagnose and resolve database performance issues at scale, including both systematic analysis across large query populations and deep-dive debugging of individual cases
- Strong understanding of algorithms, distributed systems architecture, and backend infrastructure
- Ability to rapidly onboard to complex, unfamiliar systems and deliver meaningful improvements
- Customer-focused mindset: able to translate user-reported performance problems into technical root causes and durable fixes
- Strong communication skills for working with internal and external stakeholders (including partner engineering teams at Snowflake)
- Experience with Snowflake or other cloud data warehouses
- Prior work on observability, monitoring, or telemetry platforms
- Experience with OLAP query optimization, columnar storage, or vectorized execution
- Advanced degree in Computer Science with a focus on databases or systems
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
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