refactored getting model location function

this was done because the bucket name in the main module config can be different for how the manifest file is compiled

dagger/utilities/dbt_config_parser.py

@@ -94,7 +94,7 @@ def _get_s3_task(self, node: dict) -> dict:
         table = node.get("name", "")
         task["name"] = f"{schema}__{table}_s3"
         task["bucket"] = self._default_data_bucket
-        task["path"] = self._get_model_data_location(node, schema, table)
+        task["path"] = self._get_model_data_location(node, schema, table)[1]
 
         return task
 
@@ -155,7 +155,7 @@ def _generate_dagger_tasks(
 
     def _get_model_data_location(
         self, node: dict, schema: str, dbt_model_name: str
-    ) -> str:
+    ) -> Tuple[str, str]:
         """
         Gets the S3 path of the dbt model relative to the data bucket.
         If external location is not specified in the DBT model config, then the default data directory from the
@@ -173,7 +173,10 @@ def _get_model_data_location(
         if not location:
             location = join(self._default_data_dir, schema, dbt_model_name)
 
-        return location.split(self._default_data_bucket)[1].lstrip("/")
+        split = location.split("//")[1].split("/")
+        bucket_name, data_path = split[0], "/".join(split[1:])
+
+        return bucket_name, data_path
 
     def generate_dagger_io(self, model_name: str) -> Tuple[list, list]:
         """