Lonnie Johnson
About Lonnie Johnson
Lonnie Johnson is a Data Architect with extensive experience in data management and reporting. He has worked for various companies, including Carnegie Robotics LLC and Merkle, where he developed custom processes and reporting systems to enhance business operations.
Current Role at Carnegie Robotics
Lonnie Johnson has been serving as a Data Architect at Carnegie Robotics LLC since 2018. In this role, he focuses on designing and implementing data solutions that enhance operational efficiency. He also works as a Costpoint / Visual Factory Process Developer, contributing to the integration of various data management systems. His tenure at Carnegie Robotics spans over six years, during which he has developed significant expertise in data architecture and process development.
Previous Experience in Data Management
Prior to his current position, Lonnie Johnson held various roles in data management and architecture. He worked at Merkle from 2013 to 2017, where he served as a Data Management Solution Provider and later as Reporting Data Manager and Data Architect. His responsibilities included creating intelligent stored procedures and developing SSRS reports that integrated with systems like Jira and Costpoint. He also worked briefly at Ansaldo STS and Victory Media, where he contributed to SSRS report development and data architecture.
Educational Background in Computer Science
Lonnie Johnson earned a Bachelor of Science (B.S.) in Computer Science from the University of Pittsburgh, completing his studies from 1990 to 1995. He furthered his education by obtaining a Master's degree in Information Technology from the University of Phoenix between 2001 and 2003. This educational foundation has equipped him with the skills necessary for his roles in data architecture and management.
Key Contributions and Projects
Throughout his career, Lonnie Johnson has made significant contributions to data management processes. He developed a full cash flow report system that provides real-time financial insights and projections. Additionally, he created custom processes for scheduled issue creation based on data queries, implemented business rules across various data components, and modified Jira screens to meet project requirements. His work has consistently focused on enhancing data flow and reporting capabilities.