AI-First Finance Analytics Engineer

Snowflake; United States; Hybrid; USD 180,000 - 240,000; Full time

Job summary

Snowflake is seeking an AI-driven analytics professional to join our Finance Analytics team in a hybrid role based in Menlo Park, CA. You will build AI-powered agents, data models, and Streamlit dashboards that surface real-time finance insights.

You will engineer prompts, manage skill files, and ensure outputs meet high accuracy standards while collaborating with deal desks and finance stakeholders. Strong Python/SQL and data modeling fundamentals are essential.

Qualifications

• AI-assisted development using LLM tooling and production-ready prompts.
• Structured prompts (YAML + Markdown) that route correctly most of the time.
• Modern, typed Python applications and data pipelines.
• SQL with window functions and advanced patterns.
• Understand bronze-silver-gold data modeling and how to query it.

Responsibilities

• Design and build AI agent experiences encoding finance workflows into reusable tools.
• Write and iterate on prompt and skill files based on output quality.
• Build tools enabling non-technical finance analysts to produce analyst-quality output from a single prompt.
• Evaluate model outputs rigorously as the quality gate before stakeholder delivery.
• Develop revenue, cost, and earnings analytics pipelines and dashboards.
• Automate deal desk reporting and pricing-related analytics.
• Own semantic layers and Streamlit dashboards for finance insights.

Skills

AI-assisted development

Prompt engineering and skill authoring

Python

SQL

Data modeling fundamentals

Tools

Snowflake Cortex

SnowWork / CoCo

dbt

Semantic search / embeddings

Job description

Snowflake is seeking an AI-driven analytics professional to join our Finance Analytics team in a hybrid role based in Menlo Park, CA. You will build AI-powered agents, data models, and Streamlit dashboards that surface real-time finance insights.

You will engineer prompts, manage skill files, and ensure outputs meet high accuracy standards while collaborating with deal desks and finance stakeholders. Strong Python/SQL and data modeling fundamentals are essential.