Data Engineering Intern (2027)

Post Consumer Brands•Lakeville, MN

6d•Onsite

About The Position

This is a 12-week summer internship designed to provide meaningful work, professional development, and hands-on exposure to enterprise data and technology solutions. The intern will work alongside experienced IT professionals to support the systems and processes that power data-driven decision-making across the organization. The role offers exposure to modern data platforms, cloud technologies, data warehousing, automation, and analytics, while developing technical skills for a future career in technology. The intern will have the opportunity to work with tools and technologies such as Snowflake, Azure Cloud, SQL, API, Python, Linux, enterprise data integration tools, and automation platforms while contributing to real business projects.

Requirements

Pursuing a bachelor's or master's degree in Computer Science, Management Information Systems (MIS), Data Analytics, Information Technology, Engineering, Data Science or a related field.
Expected graduation between December 2027 and August 2028.
Strong analytical, problem-solving, and communication skills.
Ability to work independently and collaborate effectively with others.
Curious, motivated, and eager to learn new technologies and solve complex problems.
Interest in data engineering, cloud technologies, analytics, or enterprise systems, with a desire to explore career opportunities with Post Consumer Brands after graduation.
Must be authorized to work in the United States without current or future visa sponsorship.

Nice To Haves

Familiarity with relational databases, SQL, or data management concepts.
Previous internship, leadership, work, research, or project experience.

Responsibilities

Support enterprise data and analytics solutions that enable data-driven business decisions.
Work with databases, cloud technologies, and automation tools to improve data processes and workflows.
Analyze, document, test, and enhance data engineering solutions.
Partner with IT and business teams to solve problems and deliver technology-driven improvements.
Analyze and optimize Oracle-based data warehouse environments and ETL processes.
Support planning and migration efforts to cloud platforms such as Snowflake.
Develop data ingestion and transformation processes for new data sources.
Identify and document opportunities to streamline data workflows and retire obsolete processes.
Participate in user testing, validation, and documentation of data engineering solutions.