[Hiring] Solutions Architect @Snowflake

Role 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.

Snowflake's Observe business unit delivers AI-powered observability at enterprise scale, unifying logs, metrics, and traces across petabytes of telemetry data into a single, trusted, Snowflake-native platform. As organizations shift from reactive monitoring to proactive, automated troubleshooting, the implementation experience becomes a critical driver of product value.

Solutions Architects are the architectural foundation of the Observe post-sales practice. They bring deep platform and observability domain expertise to design durable, scalable architectures, ensuring every enterprise implementation starts with a sound technical foundation that Implementation Engineers (IEs) execute with confidence and customers build on for years. By owning the architecture layer, and establishing shared standards that demonstrate what great looks like, Solutions Architects multiply the effectiveness of the entire go-to-market team.

This role is ideal for a technically exceptional practitioner who has moved beyond execution into architecture. Someone who can assess a complex enterprise environment, design an observability system built to scale, document it with precision, and hand it off with confidence.

Qualifications

• 8+ years in customer-facing technical roles; Solutions Architect, Staff/Principal engineer, observability engineer, or SRE; with a demonstrated shift from hands-on execution to architecture-level thinking
• Deep expertise in observability platforms and telemetry systems at scale, including data modeling tradeoffs across logs, metrics, and traces
• Strong hands-on experience with OpenTelemetry: instrumentation strategies, collector configuration, exporters, and multi-signal pipeline design
• Proven ability to design or lead migrations from commercial observability platforms (Splunk, ELK, Datadog, New Relic, Dynatrace) to modern alternatives
• Experience assessing complex enterprise environments and producing architectural designs that are durable, scalable, and practical to implement
• Solid understanding of cloud platforms (AWS, GCP, Azure), containerized workloads, and Kubernetes-based environments
• Strong communication skills; credible with both hands-on engineering teams and senior technical leadership
• Experience producing high-quality technical documentation: architecture diagrams, design decision records, runbooks, implementation plans
• Exposure to AI-assisted observability or AIOps

Requirements

• Take an active role in technical discovery on SA-attached engagements, working in tandem with the Implementation Engineer to assess existing telemetry, infrastructure, data volumes, tooling landscape, and operational requirements
• Design end-to-end observability architectures on Observe, covering telemetry ingestion, pipeline topology, data modeling, enrichment and normalization strategies, alerting design, and long-term retention
• Define the implementation approach and architecture blueprint that Implementation Engineering teams execute against
• Validate that proposed configurations, pipelines, and data models will meet production-scale requirements before execution begins
• Advise customers on OpenTelemetry adoption strategies
• Have an active role in the architecture and planning phases of enterprise engagements, working in tandem with the IE from kickoff through handoff to dedicated IE team(s)
• Produce clear, high-quality handoff artifacts (e.g. reference architectures, design decision records, implementation plans, and configuration standards)
• Remain available to Implementation teams during execution for architectural blockers, scope changes, or decisions requiring architectural judgment
• Conduct formal go-live architecture reviews to validate that the implemented solution matches the designed architecture and is production-ready
• Design the target architecture and phased cutover strategy for complex migrations from existing observability platforms (e.g., Splunk, ELK, Datadog, Dynatrace, New Relic) onto Observe, minimizing disruption to production operations
• Identify architectural gaps, data quality risks, and technical debt in existing environments; design clean, scalable replacements where appropriate
• Partner with the Director of Implementation Engineering to develop and own internal reference architectures, design documents, runbooks, and implementation standards
• Build and maintain field demo infrastructure — realistic, production-grade environments that pre-sales and IE teams use to show customers what a well-architected Observe deployment looks like
• Capture reusable patterns from field engagements and translate them into assets the broader IE team can apply consistently
• Serve as a technical authority on complex or novel customer scenarios
• Act as a force multiplier for the IE team; set the technical example, structure, and tone on an engagement, and mentor and level up junior Implementation Engineers rather than taking over their work
• Contribute beyond core Observe architecture where the engagement calls for it; integration with adjacent solutions and technologies, process (re-)engineering, and AI refactoring
• Contribute field insights back to Product and Engineering to influence the platform roadmap

Benefits

• Time-to-first-value for new Observe customers
• Customer satisfaction scores (post-engagement NPS/CSAT)
• On-time and on-scope delivery rate
• Escalation rate and time to resolution
• Observe consumption growth attributable to successful implementations