diff --git a/examples/mara_join.py b/examples/mara_join.py
new file mode 100755
index 0000000..bed79c3
--- /dev/null
+++ b/examples/mara_join.py
@@ -0,0 +1,44 @@
+#!/usr/bin/env python3
+# /// script
+# dependencies = [
+#   "arraylake",
+#   "icechunk",
+#   "xarray",
+#   "xarray-sql",
+#   "pandas",
+# ]
+# ///
+
+"""Demo of a (spatial) join using Xarray-SQL and DataFusion for MARA."""
+import pandas as pd
+import xarray as xr
+import xarray_sql as xql
+from arraylake import Client
+
+# Login and get access to EarthMover's Temporal ERA5 dataset.
+client = Client()
+client.login()
+repo = client.get_repo('earthmover-public/era5-surface-aws')
+ds = xr.open_zarr(
+    repo.readonly_session('main').store,
+    group='temporal',
+    chunks=None,
+    zarr_format=3,
+    consolidated=False,
+)
+
+# Create a DataFusion context and register the datasets as tables.
+ctx = xql.XarrayContext()
+ctx.from_dataset(
+    'era5', ds, chunks=dict(time=8736, latitude=12, longitude=12)
+)
+ctx.from_pandas(
+    pd.read_feather(
+        'https://github.com/wildlife-dynamics/ecoscope/raw/refs/heads/master/'
+        'tests/sample_data/vector/movebank_data.feather'
+    ),
+    'movebank',
+)
+
+# TODO(alxmrs): When I'm not on cellular internet, explore the datasets and write the
+#  join in SQL.