Analyst, Finance Analytics & AI - Deal Desk

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. Location: This is a hybrid role in Menlo Park, CA About the role We are an AI-first analytics team. We don't use AI to augment traditional BI workflows — we've replaced them. The Finance Analytics team builds the intelligence layer that Strategic Finance runs on: AI agents that encode repeatable finance processes, Streamlit apps that surface real-time insight, semantic models that let any analyst query complex data in plain English, and workflow automations that collapse hours of manual work into a single prompt. Our primary development environment is CoCo (Cortex Code), Snowflake's AI coding assistant, and CoWork , the AI IDE we ship work in. Every deliverable on this team is built AI-first: you design the workflow, you write the prompt, you validate the output. If you are still building dashboards by hand, refreshing Excel files manually, or treating AI as a spell-checker for your code — this role will ask you to operate differently. This is a high-breadth seat. One week you're building a deal benchmarking agent that surfaces peer comparison data for a deal desk manager seconds before a negotiation; the next you're designing a margin calculator that lets a sales rep model deal economics live on a call. You are equally comfortable in an AI-IDE, a Python file, and a stakeholder summary for a deal desk director.

AI agent and workflow development (primary focus) Design and build skills and agentic experiences that encode repeatable finance workflows — revenue analysis, cost monitoring, earnings prep, headcount tracking — into reusable, invokable tools using CoCo and CoWork Write and iterate on prompt & skill structures (YAML + Markdown skill files) based on output quality and stakeholder feedback Build skills that allows non-technical finance analysts to produce analyst-quality output in a single prompt Evaluate model outputs rigorously — you are the quality gate before anything reaches a finance stakeholder Finance analytics Build and maintain quarterly and weekly revenue summary pipelines Support sensitivity analysis models for quarterly business reviews & revenue forecast scenarios Produce ad-hoc analysis for deal desk operations — discount trend analysis, concession benchmarking, pipeline deep dives, and capacity utilization summaries for renewal planning Deal desk intelligence Build and maintain the deal benchmarking and margin analysis tools used by deal desk managers in live negotiations — accuracy directly impacts pricing decisions Develop consumption and overage analytics that surface which accounts are trending toward underage (rollover risk) or overage (expansion opportunity) ahead of their renewal Automate the quarterly deal desk reporting pack — closed deal summaries, concession trends, rip-and-replace analysis, early renewal cadence, and edition splits by service level Build and iterate on AI skills ( SKILL.md prompt files) that encode deal desk workflows: peer benchmark lookup, ACV suggestion, effective discount recommendation, and approval queue management Partner with deal desk managers to translate deal structure logic and pricing conventions into data models and AI agents that surface the right recommendation at the right moment Semantic Layer & Application development Own