Snow is an essential climate variable that is important for the hydrologic cycle, vegetation and habitat, and socioeconomics. Snow dynamics, including melt timing, are generally monitored over wide areas by satellites with low spatial (250-1000 m) and high temporal (daily) resolutions. High spatial resolution monitoring (10-30 m) has been limited to smaller extents or mountains because of computational constraints and the lack of enough cloud-free observations to make effective decisions. However, the recent production of 30 m Harmonized Landsat Sentinel-2 (HLS) with a 2–3-day temporal resolution and advances in scalable geoscience workflows provide potential for a breakthrough in snow dynamics monitoring. Here, we leverage HLS’s frequent revisits to map snow dynamics, including snow end date, across wide areas of Canada. We create products for each snow year from 2018-2019 to 2023-2024 and interannually. We provide timing uncertainties and a quality metric for all pixels. End date quality is high, with good year-to-year consistency and strong relationships with both a low spatial resolution reference and reference local-scale snow depth. HLS supports high quality wide-area snow dynamics understanding, especially at higher latitudes (with more orbit overlap) and when cloud cover is less. However, more work is required to assess all outputs in a variety of landscapes and consider potential improvements. Moving forward, we intend to build and maintain an annual Canada-wide 30 m snow dynamics product that will be available as an open-access dataset.