2 months ago
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
Solutions Engineering
About Snowflake
Snowflake builds a cloud-native data platform used by enterprises to store, integrate, share, and analyze data across AWS, Azure, and Google Cloud. Its core products span data warehousing, data lakes, data engineering, and governed data sharing, sold via consumption-based subscriptions. Founded in 2012 and publicly traded on the NYSE (SNOW) following a 2020 IPO, Snowflake supports analytics and data application workloads across industries.