Megan Tiedtke
About Megan Tiedtke
Megan Tiedtke is a Data Analyst with extensive experience in data analysis and reporting, currently working at DPR Construction since 2021. She has held various roles in organizations such as the University of North Texas, Austin Industries, and Union Pacific Railroad, and possesses expertise in ETL processes and tools like Jasper Server Reporting and Microsoft Power BI.
Work at DPR Construction
Megan Tiedtke has been employed at DPR Construction as a Data Analyst since 2021. In this role, she focuses on data analysis and reporting within the Dallas-Fort Worth Metroplex. Her responsibilities include utilizing advanced data visualization tools to support business intelligence initiatives.
Previous Experience in Data Analysis
Prior to her current position, Megan worked at Austin Industries as a BI Programmer/Analyst from 2018 to 2021. She also held the role of Programmer/Analyst at the University of North Texas from 2014 to 2015 and at Creighton University from 2009 to 2014. These roles contributed to her expertise in data analysis and reporting.
Education and Expertise
Megan Tiedtke earned a Bachelor of Science in Management Information Systems from the University of Nebraska at Omaha, completing her studies from 2005 to 2009. She later obtained a Master of Business Administration and a Master's in IT Management from Creighton University, studying from 2010 to 2013. Her educational background supports her skills in data analysis and business intelligence.
Technical Skills in Data Management
Megan is skilled in Extract, Transform, Load (ETL) processes, which enhance data integration and management. She utilizes Jasper Server Reporting for data analysis and report building, and employs Microsoft Power BI for advanced data visualization and business intelligence reporting.
Internship Experience
Megan began her career as a Customer Product Development Intern at Union Pacific Railroad, where she worked for one year from 2008 to 2009. This internship provided her with foundational experience in data-related roles.