Performance analysis is critical for pinpointing bottlenecks in applications. Many different profilers exist to instrument parallel programs on HPC systems, however, there is a lack of tools for analyzing such data programmatically. Hatchet, an open-source Python library, can read profiling data from several tools, and enables the user to perform a variety of analyses on hierarchical performance data. In this paper, we augment Hatchet to support new features: a syntax query language for representing call path-related queries, visualizations for displaying and interacting with the structured data, and new operations for performing analysis on multiple datasets. Additionally, we present performance optimizations in Hatchet's HPCToolkit reader and the unify operation to enable scalable analysis of large profiles.