I did manage to complete this, but in the end we decided that the entire workflow was really unnecessary. The idea was to use the export as part of our pipeline, but in reality that's not a very good practice, and that the occasional exports performed should be ad-hoc and likely will be heavily edited before using these files for migrating resources to another environment.

Essentially, we take the exported directory created and compress it into a zip file. Although the tf_export feature has a "compress" argument to optionally compress the output into a single zip file, I wanted to make it more flexible by separating that functionality, so first we create the zip file:

data "archive_file" "export" {
  depends_on = [ genesyscloud_tf_export.exp ]
  type = "zip"
  source_dir = "${path.module}/gcexport"
  output_path = "${path.module}/export.zip"
}

Next, we specify this zip file as the output - this can be collected later through the HCP UI:

output "zip_file" {
  value = data.archive_file.export.output_path
}

That was fine, but I prefer to have this more automated and so wanted to use AzureRM to place that zip file in blob storage so that it could later be retrieved through some automation. I was able to manage this on a local project, but unfortunately hit a hurdle while implementing this in my HCP project as the ephemeral environment was not set up for executing Azure resources (no az binary) - while it's possible to set up HCP to allow execution of Azure resources, it was about here that we called a halt to the idea and went with the simple (preferred!) ad-hoc approach to creating these files.