diff --git a/bigframes/session/bigquery_session.py b/bigframes/session/bigquery_session.py
index ae8dc88d43..883087df07 100644
--- a/bigframes/session/bigquery_session.py
+++ b/bigframes/session/bigquery_session.py
@@ -84,7 +84,9 @@ def create_temp_table(
 
             ddl = f"CREATE TEMP TABLE `_SESSION`.{googlesql.identifier(table_ref.table_id)} ({fields_string}){cluster_string}"
 
-            job = self.bqclient.query(ddl, job_config=job_config)
+            job = self.bqclient.query(
+                ddl, job_config=job_config, location=self.location
+            )
             job.result()
             # return the fully qualified table, so it can be used outside of the session
             return job.destination
@@ -94,7 +96,10 @@ def close(self):
             self._sessiondaemon.stop()
 
         if self._session_id is not None and self.bqclient is not None:
-            self.bqclient.query_and_wait(f"CALL BQ.ABORT_SESSION('{self._session_id}')")
+            self.bqclient.query_and_wait(
+                f"CALL BQ.ABORT_SESSION('{self._session_id}')",
+                location=self.location,
+            )
 
     def _get_session_id(self) -> str:
         if self._session_id:
diff --git a/tests/system/large/test_location.py b/tests/system/large/test_location.py
index d4428c1f95..3ebe2bb040 100644
--- a/tests/system/large/test_location.py
+++ b/tests/system/large/test_location.py
@@ -14,8 +14,6 @@
 
 import typing
 
-from google.cloud import bigquery
-from google.cloud.bigquery_storage import types as bqstorage_types
 import pandas
 import pandas.testing
 import pytest
@@ -41,7 +39,15 @@ def _assert_bq_execution_location(
     if expected_location is None:
         expected_location = session._location
 
-    assert typing.cast(bigquery.QueryJob, df.query_job).location == expected_location
+    query_job = df.query_job
+    assert query_job is not None
+    assert query_job.location == expected_location
+    destination = query_job.destination
+    assert destination is not None
+    destination_dataset = session.bqclient.get_dataset(
+        f"{destination.project}.{destination.dataset_id}"
+    )
+    assert destination_dataset.location == expected_location
 
     # Ensure operation involving BQ client suceeds
     result = (
@@ -52,38 +58,28 @@ def _assert_bq_execution_location(
         .head()
     )
 
-    assert (
-        typing.cast(bigquery.QueryJob, result.query_job).location == expected_location
+    # Use allow_large_results = True to force a job to be created.
+    result_pd = result.to_pandas(allow_large_results=True)
+
+    query_job = df.query_job
+    assert query_job is not None
+    assert query_job.location == expected_location
+    destination = query_job.destination
+    assert destination is not None
+    destination_dataset = session.bqclient.get_dataset(
+        f"{destination.project}.{destination.dataset_id}"
     )
+    assert destination_dataset.location == expected_location
 
     expected_result = pandas.DataFrame(
         {"number": [444, 222]}, index=pandas.Index(["aaa", "bbb"], name="name")
     )
     pandas.testing.assert_frame_equal(
-        expected_result, result.to_pandas(), check_dtype=False, check_index_type=False
-    )
-
-    # Ensure BQ Storage Read client operation succceeds
-    table = result.query_job.destination
-    requested_session = bqstorage_types.ReadSession(  # type: ignore[attr-defined]
-        table=f"projects/{table.project}/datasets/{table.dataset_id}/tables/{table.table_id}",
-        data_format=bqstorage_types.DataFormat.ARROW,  # type: ignore[attr-defined]
-    )
-    read_session = session.bqstoragereadclient.create_read_session(
-        parent=f"projects/{table.project}",
-        read_session=requested_session,
-        max_stream_count=1,
+        expected_result,
+        result_pd,
+        check_dtype=False,
+        check_index_type=False,
     )
-    reader = session.bqstoragereadclient.read_rows(read_session.streams[0].name)
-    frames = []
-    for message in reader.rows().pages:
-        frames.append(message.to_dataframe())
-    read_dataframe = pandas.concat(frames)
-    # normalize before comparing since we lost some of the bigframes column
-    # naming abtractions in the direct read of the destination table
-    read_dataframe = read_dataframe.set_index("name")
-    read_dataframe.columns = result.columns
-    pandas.testing.assert_frame_equal(expected_result, read_dataframe)
 
 
 def test_bq_location_default():