Brian Haas
About Brian Haas
Brian Haas is a Principal Database Engineer at CoverMyMeds, where he has worked since 2022. He previously held roles as Database Architect and Principal of Financial Software Development at the same company, contributing to significant data management improvements and compliance efforts.
Work at CoverMyMeds
Brian Haas has held multiple roles at CoverMyMeds since 2014. He initially served as a Database Architect from 2014 to 2018, where he contributed to various database solutions. From 2018 to 2022, he worked as Principal in Financial Software Development, focusing on financial compliance projects. Since 2022, he has been employed as a Principal Database Engineer, continuing to enhance the company's data infrastructure. His work involves both server design and collaboration with various teams, ensuring efficient data management and compliance.
Education and Expertise
Brian Haas earned a Bachelor of Arts (BA) in Philosophy from The Ohio State University, studying from 1999 to 2005. His educational background provides a foundation for critical thinking and problem-solving, which he applies in his technical roles. His expertise includes database architecture, financial software development, and data engine design, showcasing his ability to integrate complex systems and optimize performance.
Background
Brian Haas has a professional background that spans over a decade in database engineering and software development. He has worked extensively in roles that require both technical and analytical skills. His experience at CoverMyMeds highlights his ability to manage large-scale data projects and collaborate with cross-functional teams to achieve compliance and operational efficiency.
Achievements
During his tenure at CoverMyMeds, Brian Haas architected a significant data consolidation effort aimed at ensuring Sarbanes-Oxley (SOx) financial compliance. He designed and implemented an asynchronous, self-healing, dependency-aware data engine (ACE), which dramatically reduced data lag from nearly 12 hours to less than 10 minutes. Additionally, he optimized the primary data server utilized by nearly 100 analysts and data engineers, leading to a reduction in overall load by more than 30%.