Mark Stevens
About Mark Stevens
Mark Stevens is a Senior Data Warehouse and Data Integration Architect at George Washington University, where he has worked since 2012. He specializes in data integration between on-premises ERP systems and cloud applications, utilizing technologies such as Neo4j and Informatica.
Current Role at George Washington University
Mark Stevens serves as the Senior Data Warehouse and Data Integration Architect at George Washington University. He has held this position since 2012 and is based in Ashburn, VA. In this role, he leads the data integration center of excellence, focusing on designing and developing data integrations between on-premises ERP systems and cloud applications. His work involves utilizing advanced technologies to enhance data management and integration processes within the university.
Previous Experience at George Washington University
Prior to his current role, Mark Stevens worked at George Washington University as a Senior Payroll / Finance Data Analyst from 2011 to 2012. He also served as the HRIS Project Manager from 2008 to 2011. During his tenure, he contributed to various data management initiatives and played a key role in optimizing payroll and finance data processes.
Education and Certifications
Mark Stevens has a strong educational background in technology and management. He studied at Indiana University of Pennsylvania, where he earned a Master of Arts in Adult Education / Communications Technology and a Bachelor of Science in Business Management. He also holds a Database Administration Certificate from the University of Illinois Urbana-Champaign and an Application Programming Career Studies Certificate from Northern Virginia Community College.
Data Integration Expertise
Mark Stevens specializes in developing data integrations through point-to-point integrations and web APIs. He has extensive experience using Informatica PowerCenter and Informatica Cloud for data integration projects. Additionally, he utilizes graph database applications, specifically Neo4j, to facilitate the analysis of complex data sets, enhancing the university's data capabilities.