Quantitative Susceptibility Mapping (QSM) is a post-processing technique applied to gradient-echo phase data. QSM generally requires a signal mask to identify reliable phase values before reconstruction. Most QSM pipelines do not include masking procedures, and often suggest masking techniques that introduce artefacts, work only in the human brain, and lose critical information, especially near strong susceptibility sources. We propose two novel echo-dependent masking strategies and find that they significantly reduce streaking artefacts, particularly surrounding strong sources and tissue boundaries in multi-echo data. Our techniques are open-source and implemented in a new framework for automated, scalable, and robust QSM processing.