Business Intelligence Analyst

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.

Job Location: 135 Constitution Drive, Menlo Park, CA 94025.

ELT: Data Analytics and AI

REQ ID: ASHREQ-8304

Joining this team means architecting the performance, scalability, and service infrastructure that will empower the world's largest enterprises to seamlessly govern their transactional and analytical data in one place. If you are passionate about building industry-leading technologies that solve real-world scale and performance problems, this is the place to be. In this role, you will be a key contributor to the evolution of our core product: an elastic, large-scale, high-performance data processing system. We are looking for smart, enthusiastic engineers who can quickly master complex technical areas and are passionate about building new, industry-leading technologies.

AS A BUSINESS INTELLIGENCE ANALYST, PRODUCT FINANCE (MULTIPLE POSITIONS AVAILABLE) AT SNOWFLAKE, YOU WILL:

Serve on the Finance BI team and partner with Product Finance to deliver business intelligence reporting that supports Engineering and Finance teams. Product Finance analyzes costs associated with the development of Snowflake’s product, in particular, cloud spend. Develop applications and manage data pipelines that power financial reporting, streamline QBR workflows, and surface actionable insights that will optimize spending at Snowflake. Collaborate with analysts across Finance on quarterly ad-hoc analyses utilizing SQL, Python, and BI tools, as well as data best practices and stakeholder engagement. Design and develop AI-driven solutions to automate financial workflows, analyses, and insight generation. Responsible for building machine learning and generative AI models to identify cost anomalies, forecast cloud spend, and recommend optimization strategies. Develop scalable data models and agentic automation frameworks that autonomously gather data, execute multi-step analyses, and generate executive-ready insights, while integrating Python-based analytical and ML workflows into production BI environments. Collaborate cross-functionally with Finance, Engineering, and Data teams to deploy AI-enabled applications that improve operational efficiency, reduce manual analysis, and enhance strategic planning. Telecommuting permitted.

Minimum Requirements for Position:

• Master’s degree or foreign equivalent in Business Analytics, Business Intelligence or related field, and 1 year of experience in the job offered or related occupation.

Education or experience must include:

• Utilizing SQL, including analyzing data, standardizing queries, and building large-scale relational datasets.

• Utilizing Python and application development, with an emphasis on scalability and user experience.

• Developing and deploying enterprise-grade Business Intelligence (BI) tools, such as Streamlit, Tableau or Looker

• Utilizing AI and AI prompt development

The base salary range for this role is $142,438 - $150,150

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

How do you want to make your impact?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: