Principal Software Engineer - Performance Engineering (Cloud Infrastructure) at Snowflake — Edison, USA | Base Career

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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.

Principal Software Engineer — Performance Engineering (Cloud Infrastructure)

Engineering Location: Menlo Park

About the Team

The Capacity, Performance & Efficiency team sits at the intersection of cloud hardware, workload behavior, performance measurement, and business economics.

We drive Snowflake’s cloud hardware adoption and evolution strategy, price/performance decisions, platform footprint expansion amidst capacity constraints, and strategic alignment with cloud service provider (CSP) technical roadmaps.

We're looking for a Principal Performance Engineer to drive Snowflake's cloud infrastructure performance strategy.

This is a high-autonomy, high-impact role for someone who can go deep on hardware internals (CPU microarchitecture, memory bandwidth, I/O behavior) while also translating that technical depth into pricing, capacity, and roadmap decisions across Snowflake.

You will drive the evaluation of new hardware generations across all major cloud providers, build the benchmarking and modeling infrastructure that turns raw performance data into pricing and rollout decisions, and represent Snowflake in technical discussions with CSPs and silicon partners.

You'll help grow performance engineering as a discipline across the company — mentoring engineers, building benchmark capability, and championing a culture of rigorous, data-driven performance work.

Own new hardware evaluation and enablement.

Lead evaluation of new AWS, Azure, and GCP instance types (e.g., Graviton, AMD Turin, Azure ARM/Cobalt, GCP Axion) by building representative benchmark and evaluation solutions.

Set performance strategy and architecture.

Shape the team's technical roadmap, set direction on measurement methodology, and translate benchmark results into concrete rollout and adoption recommendations.

Lead cross-functional and CSP partnerships.

Work across engineering (i.e.

Warehouse, Capacity, and other core platform teams) and Finance along with AWS, Azure, GCP to qualify new hardware and influence future cloud-instance designs.

Characterize hardware performance at a deep level.

Analyze CPU microarchitecture (e.g., memory bandwidth, PMU counters, I/O behavior) to identify workload-specific bottlenecks and drive resolution.

Develop price/performance model to support new hardware transitions.

Automate day-zero hardware readiness.

Build automated performance-validation workflows and per-provider/per-instance scorecards so Snowflake can qualify and price new silicon at or near cloud-provider GA.

Grow the performance engineering discipline.

Mentor engineers, build out benchmarking capability, and drive company-wide performance education (e.g., a recurring Performance Tech Talk series).

Our ideal candidate will have:

12+ years of experience in performance engineering, systems engineering, or infrastructure engineering, with a track record of principal-level technical leadership.

Deep expertise in cloud infrastructure performance across at least one major CSP (AWS, Azure, or GCP), including instance types, pricing models, and capacity constraints.

Strong grounding in hardware/systems fundamentals: CPU microarchitecture, memory bandwidth, I/O subsystems, and use of profiling tools (PMU counters, etc.) to root-cause performance bottlenecks.

building or operating large-scale benchmarking systems (e.g., TPC-DS-style workloads) and turning benchmark output into actionable pricing/rollout decisions.

Ability to build quantitative models connecting technical performance metrics to business outcomes (pricing multipliers, cost-per-query).

A track record of leading cross-functional, cross-company initiatives — comfortable being the primary technical point of contact with external hardware and cloud partners (CSPs, silicon vendors).

Bias toward automation: builds scorecards, dashboards, and validation pipelines rather than relying on one-off analysis.

Nice to Have

Experience with data warehouse / distributed database performance characteristics.

Direct experience partnering with cloud providers or silicon vendors on early-access hardware programs.

Principal Software Engineer - Performance Engineering (Cloud Infrastructure)

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Engineering Location: Menlo Park

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