Analytics Engineer - Finance

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.

About Snowflake

Snowflake started with a clear vision: develop a cloud data platform that is effective, affordable, and accessible to all data users. Snowflake developed an innovative new product with a built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions. We are now a global, world-class organization with offices in more than a dozen countries and serving many more.

This role requires in-person attendance in our Pune office at least 3 days per week.

Job Description

We are looking for an Analytics Engineer to join our growing Finance Analytics Engineering team. In this role, you will drive value and empower decision-making by developing and maintaining the data infrastructure which fuels reporting and analysis for the Finance organization and has a direct impact on Snowflake’s success as a company. As an Analytics Engineer, you will be responsible for the following:

• Use SQL, Python, Snowflake, dbt, Airflow, and other systems while working within an agile development model to build and maintain data infrastructure for use in reporting, analysis, and automation

• Perform data QA and develop automated testing procedures for use with Snowflake data models

• Translate reporting, analysis, and automation requirements into data model requirements and specifications

• Work with IT and other technical stakeholders to source data from key business systems and Snowflake databases