At Banner Solutions, we're obsessed with making our customers' jobs easier through innovative inventory availability, product findability, and top-tier customer support. Our expertise spans commercial, electronic access control, residential hardware, and locksmith supplies, backed by an industry-leading e-commerce platform featuring products from over 260 manufacturers. We aim to set new standards in the industry by streamlining processes and delivering personalized service. Currently, we're entering an exciting phase of growth and expansion supported by significant investments. Job Description We're seeking a highly analytical Power BI Engineer to join our team as a business partner for data-driven decision-making across Banner. • Collaborate with business leaders to centralize and drive data usage across the organization. • Develop and maintain Power BI datasets, reports, dashboards, and visualizations. • Extract, transform, and load (ETL) data from a data lake into Power BI for reporting. • Design efficient data models and use Power Query (M) and DAX to manipulate data for reporting needs. Required Skills and Qualifications To succeed in this role, you'll need: • A Bachelor's degree in Computer Science, Data Science, Information Systems, or related field. • 3+ years of experience with Power BI development and data analysis. • Experience working with data lakes (Azure Data Lake, AWS S3, etc.). • Strong proficiency in DAX, Power Query (M), and data modeling. What You'll Gain • Ownership shares in the company. • 401K match. • Unlimited PTO. • Employee Discounts through our partners. • Health, dental, and vision insurance coverage. • Mentorship & Leadership Development.
Job Type
Fulltime role
Skills required
No particular skills mentioned.
Location
Chicago, Illinois
Salary
No salary information was found.
Date Posted
April 13, 2025
Banner Solutions is seeking a Power BI Developer and Analyst to enhance data-driven decision-making. The role involves developing Power BI reports and collaborating with business leaders to centralize data usage.