Researchers shouldn't have to spend time searching for, accessing and reading data. They should be able to start doing science quickly and efficiently. A critical step in "doing science faster" is reducing the cognitive load of search-, access- and read-steps of science workflows by using simple tools that load data as familiar, easy to use data structures. The Data Use and Education Team at NSIDC-DAAC are developing software tools and education resources to facilitate and teach data access patterns for cryospheric data. In this poster we demonstrate access patterns for ICESat-2 data using the popular earthaccess and xarray Python packages. The ICESat-2 mission measures Earth surface heights with a photon-counting lidar. Multiple products are created for land ice, sea ice, vegetation and ocean surface heights. The datasets are large and complex. The combination of earthaccess and xarray enable quick access to the data whether researchers are working in the cloud or on local machines. Data can either be downloaded or "streamed" as familiar files or virtual data cubes. These access patterns, along with tools and workflows for transforming and plotting other NSIDC data, are being collected into a NSIDC Data Cookbook. This cookbook will provide reference guides on data formats, structures, and coordinate reference systems, long-form tutorials and "quick-hit" data recipes for NSIDC data.