DATA ANALYST INTERN

Galloway Company•Neenah, WI

48d

About The Position

The Data Analyst Intern will assist in advancing Galloway Company’s data analytics journey by helping transform raw data from our ERP system and spreadsheets into actionable insights. This role will support the creation of dashboards and reports using Microsoft Power BI and other data visualization tools. The ideal candidate has a strong interest in data analysis, enjoys problem-solving, and is eager to learn how data can drive decision-making within a manufacturing environment.

Requirements

Currently pursuing a 2-year degree in Data Analytics, Information Systems, Computer Science, or a related field.
Strong proficiency in Microsoft Excel (pivot tables, formulas, data manipulation).
Basic understanding of relational databases and data structures.
Interest in data visualization and analytics using tools such as Power BI.
Analytical mindset and strong attention to detail.
Excellent written and verbal communication skills.

Nice To Haves

Pursuing or holding a 4-year degree in Data Analytics, Computer Science, Information Systems, or related field.
Familiarity with ERP systems (experience with Aptean Ross or similar a plus).
Experience writing basic SQL queries.
Exposure to cloud platforms (Microsoft Azure preferred).
Experience working with manufacturing or business process data.

Responsibilities

Assist in collecting, cleaning, and organizing data from multiple sources, including ERP systems and Excel spreadsheets.
Develop and maintain Power BI dashboards and reports to visualize business performance metrics.
Work with IT and business stakeholders to define reporting requirements and ensure data accuracy.
Support data integration efforts, including working with datasets from production, sales, inventory, and finance.
Document data models, report logic, and dashboard usage for ongoing support and improvement.
Collaborate with the IT team to explore new tools and methods for analytics, automation, and data visualization.
Participate in meetings and provide insight into trends or anomalies observed in data.

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