Effective resource scheduling is critical in high-performance (HPC) and high-throughput computing (HTC) environments, where traditional scheduling systems struggle with resource contention, data locality, and fault tolerance. Meta-scheduling, which abstracts multiple schedulers for unified job allocation, addresses these challenges. Galaxy, a widely used platform for data-intensive computational analysis, employs the \textit{Total Perspective Vortex (TPV)} system for resource scheduling. With over 550,000 users, Galaxy aims to optimize scheduling efficiency in large-scale environments. While TPV offers flexibility, its decision-making can be enhanced by incorporating real-time resource availability and job status. This paper introduces the TPV Broker, a meta-scheduling framework that integrates real-time resource data to enable dynamic, data-aware scheduling. TPV Broker enhances scalability, resource utilization, and scheduling efficiency in Galaxy, offering potential for further improvements in distributed computing environments.