Base Salary
$160k - $210k/yr
Responsibilities
- Lead technical discovery for enterprise engagements by assessing telemetry, infrastructure, data volumes, tools, and operational requirements.
- Design scalable end-to-end observability architectures covering ingestion, pipeline topology, data modeling, enrichment, normalization, alerting, and retention.
- Define architecture blueprints and implementation approaches for Implementation Engineering teams.
- Validate configurations, pipelines, data models, and production-scale requirements before implementation.
- Advise customers on OpenTelemetry adoption and observability architecture strategies.
- Produce reference architectures, design decision records, implementation plans, configuration standards, runbooks, and other handoff artifacts.
- Support Implementation teams with architectural decisions, blockers, scope changes, and go-live architecture reviews.
- Design phased migration strategies from Splunk, ELK, Datadog, Dynatrace, and New Relic to Observe.
- Identify architectural gaps, data quality risks, and technical debt and design scalable replacements where appropriate.
- Develop internal standards, reusable implementation patterns, and field enablement assets with Implementation Engineering leadership.
- Build and maintain production-grade demo and lab environments for pre-sales and Implementation Engineering teams.
- Serve as a technical authority on complex customer scenarios and mentor junior Implementation Engineers.
- Contribute to adjacent solution integrations, process re-engineering, AI refactoring, and product roadmap feedback.
Requirements
- 8+ years of experience in customer-facing technical roles such as Solutions Architect, Staff or Principal Engineer, observability engineer, or SRE.
- Deep expertise in observability platforms and telemetry systems at scale, including logs, metrics, traces, and data-modeling tradeoffs.
- Strong hands-on OpenTelemetry experience, including instrumentation strategies, collector configuration, exporters, and multi-signal pipelines.
- Experience designing or leading migrations from commercial observability platforms to modern alternatives.
- Ability to assess complex enterprise environments and produce durable, scalable, practical architecture designs.
- Understanding of AWS, GCP, Azure, containerized workloads, and Kubernetes environments.
- Strong communication skills with engineering teams and senior technical leaders.
- Experience producing technical documentation such as architecture diagrams, design decision records, runbooks, and implementation plans.
- Exposure to AI-assisted observability or AIOps.
- Preferred: background in SRE, platform engineering, or DevOps and experience operating production observability at scale.
- Preferred: experience authoring internal standards, reference architectures, and enablement content.
- Preferred: experience building demo or lab environments for internal field teams.
- Preferred: familiarity with Kubernetes-native observability and cloud-native monitoring tooling.
- Preferred: experience with professional services organizations or direct experience with Observe.
Benefits
- The posting directs U.S.-based candidates to Snowflake Careers for salary and benefits information.
Tech Stack
Categories
About Snowflake
**Snowflake is proud to be the Official Data Collaboration Provider for LA28 and Team USA.** Snowflake delivers the AI Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the AI Data Cloud, organizations unite their siloed data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds. Snowflake’s platform is the engine that powers and provides access to the AI Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing. Join Snowflake customers, partners, and data providers already taking their businesses to new frontiers in the AI Data Cloud.