Intern- Data Analytics Engineer

This internship is not eligible for relocation assistance. Local candidates preferred.

Zions Bancorporation’s Internship and Banker Development Program positions are not eligible for employment visa sponsorship (e.g., H-1B visa). This includes, for example, situations where a candidate may have temporary work authorization while enrolled in school or upon graduation (e.g., CPT, OPT) but would need H-1B visa sponsorship within a few years of employment in order to maintain employment eligibility.

Zions Bancorporation is transforming what it means to work for a financial institution. We operate in a fast-paced, information-driven environment, which means we need people who bring diverse experiences, perspectives, and expertise to meet ever-changing demands. Your ability to adapt, learn innovate and collaborate with a dynamic team helps us provide exceptional service to our customers and communities.

ETO is committed to helping our employees grow, develop and advance in their career. Our Workforce of the Future, DEI and Upskilling initiatives allow you to network across the organization, volunteer in our community, and build your technical and soft skills. We believe that investing in your success and well-being is an investment in our customers and our business.

Together we are building a culture that values diversity, celebrates growth and creates a space of belonging for all our team members. Our people are what set us apart and make us great.

Zions Enterprise Data & Analytics is looking for a Data Analytics Engineering Intern.

The intern will assist the Enterprise Data Warehouse function to acquire, process, and analyze data from Enterprise Data Warehouse, Data Lake, and other data repositories to support financial or analytical reporting.

The Data Analyst Intern will:

Apply business analytics to define, identify, and obtain source data from various sources such as Enterprise Data Warehouse, Data Lake, and other enterprise platforms; analyze, map, transform, and validate data to support Financial Data Management reporting.

Leverage AI-enabled technologies to enhance data discovery, documentation, metadata management, and analytical productivity. Evaluate opportunities to develop and utilize Model Context Protocol (MCP) services and integrations to provide secure, reusable access to enterprise data and business knowledge.