diff --git a/src/hdmf_zarr/backend.py b/src/hdmf_zarr/backend.py
index 2d5538bc..b31178d6 100644
--- a/src/hdmf_zarr/backend.py
+++ b/src/hdmf_zarr/backend.py
@@ -1050,13 +1050,18 @@ def write_dataset(self, **kwargs):  # noqa: C901
                         new_dtype.append((field['name'], self.__resolve_dtype_helper__(field['dtype'])))
                 dtype = np.dtype(new_dtype)
 
+                object_codec = self.__codec_cls()
+                if not isinstance(object_codec, numcodecs.Pickle):
+                    print(f'Resorting to Pickle codec for dataset {name} of {parent.name}')
+                    object_codec = numcodecs.Pickle()
+
                 # cast and store compound dataset
                 arr = np.array(new_items, dtype=dtype)
                 dset = parent.require_dataset(
                     name,
                     shape=(len(arr),),
                     dtype=dtype,
-                    object_codec=self.__codec_cls(),
+                    object_codec=object_codec,
                     **options['io_settings']
                 )
                 dset.attrs['zarr_dtype'] = type_str
@@ -1268,6 +1273,23 @@ def __list_fill__(self, parent, name, data, options=None):  # noqa: C901
         else:
             data_shape = get_data_shape(data)
 
+        # Let's check to see if we have a structured array somewhere in the data
+        # If we do, then we are going to resort to pickling the data and
+        # printing a warning.
+        has_structured_array = False
+        if dtype == object:
+            for c in np.ndindex(data_shape):
+                o = data
+                for i in c:
+                    o = o[i]
+                if isinstance(o, np.void) and o.dtype.names is not None:
+                    has_structured_array = True
+        if has_structured_array:
+            object_codec = io_settings.get('object_codec')
+            if not isinstance(object_codec, numcodecs.Pickle):
+                print(f'Warning: Resorting to Pickle codec for {name} of {parent.name}.')
+                io_settings['object_codec'] = numcodecs.Pickle()
+
         # Create the dataset
         dset = parent.require_dataset(name, shape=data_shape, dtype=dtype, **io_settings)
         dset.attrs['zarr_dtype'] = type_str
diff --git a/tests/unit/base_tests_zarrio.py b/tests/unit/base_tests_zarrio.py
index d142499d..98b149bb 100644
--- a/tests/unit/base_tests_zarrio.py
+++ b/tests/unit/base_tests_zarrio.py
@@ -17,7 +17,7 @@
 
 # Try to import numcodecs and disable compression tests if it is not available
 try:
-    from numcodecs import Blosc, Delta, JSON
+    from numcodecs import Blosc, Delta, JSON, Pickle
     DISABLE_ZARR_COMPRESSION_TESTS = False
 except ImportError:
     DISABLE_ZARR_COMPRESSION_TESTS = True
@@ -491,12 +491,12 @@ def setUp(self):
     #  ZarrDataIO general
     #############################################
     def test_set_object_codec(self):
-        # Test that the default codec is the Pickle store
+        # Test that the default codec is JSON
         tempIO = ZarrIO(self.store, mode='w')
-        self.assertEqual(tempIO.object_codec_class.__qualname__, 'Pickle')
-        del tempIO  # also calls tempIO.close()
-        tempIO = ZarrIO(self.store, mode='w', object_codec_class=JSON)
         self.assertEqual(tempIO.object_codec_class.__qualname__, 'JSON')
+        del tempIO  # also calls tempIO.close()
+        tempIO = ZarrIO(self.store, mode='w', object_codec_class=Pickle)
+        self.assertEqual(tempIO.object_codec_class.__qualname__, 'Pickle')
         tempIO.close()
 
     def test_synchronizer_constructor_arg_bool(self):