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Snowflake's Finance Analytics & AI team is building an AI-first intelligence layer for Strategic Finance. This role sits at the intersection of finance operations, data engineering, and AI agent development—replacing traditional BI workflows with AI-native solutions.
You'll design and build AI agents and skills that encode repeatable finance processes: revenue analysis, cost monitoring, earnings prep, headcount tracking, and deal desk operations. Your primary development environment is Snowflake's CoCo (Cortex Code) AI coding assistant and CoWork IDE. Every deliverable is built AI-first: you design the workflow, write the prompt, validate the output.
Key responsibilities include:
**AI Agent & Workflow Development**: Design skills and agentic experiences using CoCo and CoWork. Write and iterate on prompt structures (YAML + Markdown skill files) based on output quality. Build skills that enable non-technical analysts to produce analyst-quality output in a single prompt. Serve as the quality gate for model outputs before they reach finance stakeholders.
**Finance Analytics**: Build and maintain quarterly and weekly revenue summary pipelines. Support sensitivity analysis models for business reviews and revenue forecasting. Produce ad-hoc analysis for deal desk operations—discount trends, concession benchmarking, pipeline deep dives, capacity utilization summaries.
**Deal Desk Intelligence**: Build and maintain deal benchmarking and margin analysis tools used in live negotiations. Develop consumption and overage analytics to surface underage (rollover risk) and overage (expansion opportunity) accounts. Automate quarterly deal desk reporting packs. Build AI skills that encode deal desk workflows: peer benchmarking, ACV suggestions, discount recommendations, approval queue management.
**Semantic Layer & Application Development**: Own semantic layers end-to-end—model design, versioning, query coverage, accuracy iteration. Develop and deploy production finance dashboards as Streamlit apps. Build customer-facing demo applications for Sales and Field teams.
**Earnings & Reporting Automation**: Participate in quarterly earnings prep—scenario tooling, export automation, IR data requests. Build and maintain source-of-truth reporting exports. Support ad-hoc disclosure and investor relations needs.
This is a high-breadth seat. One week you're building a deal benchmarking agent; the next you're designing a margin calculator for live deal modeling. You're equally comfortable in an AI-IDE, Python files, and stakeholder summaries.
Required skills: Demonstrated daily use of LLM coding assistants (CoCo, Cursor, GitHub Copilot, Claude) as your primary development tool. Ability to write structured prompts (YAML + Markdown) that route correctly 95% of the time and encode domain logic into reusable, parameterized skills. Modern, type-hinted Python for applications, data pipelines, and reporting automation. Understanding of caching, session state, and multi-page app architecture.
