Metabolomics analysis provides a detailed snapshot of small molecules present in a biological system at a given instant. It can be used to understand biological processes, diagnose disease, or understand response to environments. Although there are well-established general workflows for analyzing metabolome data, there is still a lack of comprehensive, integrated software solutions that effectively streamline this process within the Julia software ecosystem. BigRiverMetabolomics.jl is an open-source Julia package designed as an end-to-end platform for metabolomics data analysis. It includes built-in modules for data preprocessing, statistical analysis, and visualization, facilitating rapid and reproducible exploration of large-scale datasets. This talk will present the package's architecture, outline the key design principles that guided its development, and demonstrate its application using a real-world metabolomics dataset.