Snowflake20.04.2026

Analyst/Sr Analyst, Finance Analytics & AI

Полная занятостьUS-CA-Menlo Park

Обязанности

  • 01Design and build skills and agentic experiences that encode repeatable finance workflows into reusable, invokable tools using CoCo and SnowWork
  • 02Write and iterate on prompt & skill structures (YAML + Markdown skill files) based on output quality and stakeholder feedback
  • 03Build skills that allows non-technical finance analysts to produce analyst-quality output in a single prompt
  • 04Evaluate model outputs rigorously
  • 05Build and maintain quarterly and weekly revenue summary pipelines
  • 06Support sensitivity analysis models for quarterly business reviews & revenue forecast scenarios
  • 07Produce ad-hoc analysis for Strategic Finance
  • 08Build and improve semantic data models that expose finance tables to natural language queries via Cortex Analyst
  • 09Develop and deploy production finance dashboards as Streamlit apps (locally and deployed to Snowflake)
  • 10Build customer-facing demo applications for Sales and Field teams
  • 11Apply reusable component patterns and shared utility libraries for consistent, polished UI
  • 12Participate in quarterly earnings cycle prep — scenario tooling, export automation, IR data requests
  • 13Build and maintain source-of-truth reporting exports (multi-tab Excel, formatted to spec)
  • 14Support ad-hoc disclosure and investor relations data needs during quarter-end

Требования

  • 01AI-assisted development — You have used an LLM coding assistant as your primary development tool
  • 02You know how to write a prompt that produces production-ready output, how to steer a model that's heading in the wrong direction, and how to encode domain logic into a reusable, parameterized skill
  • 03You have a measurable, trackable record of daily AI usage
  • 04Prompt engineering and skill authoring — You can write a structured prompt (YAML + Markdown or equivalent) that routes correctly 95% of the time, handles edge cases gracefully, and encodes enough domain knowledge that the model behaves like a subject matter expert
  • 05You think in terms of context, instructions, examples, and output format
  • 06Python — Modern, type-hinted, readable. You write Python-based applications, data pipelines, and reporting automation. You understand caching, session state, and how to structure a multi-page app cleanly
  • 07SQL — CTEs, window functions, incremental pipeline patterns. You don't look up the syntax for a row-numbered deduplication
  • 08Data modeling fundamentals — You understand semantic layers, and how to build a model that a non-technical user can query in plain English
  • 09You are the translation layer between what the model produces and what financial stakeholders understand

Условия

  • 01Location: Menlo Park, CA