diff --git a/tests/io/delta_lake/conftest.py b/tests/io/delta_lake/conftest.py
index ff47bd9db0..40b2befe93 100644
--- a/tests/io/delta_lake/conftest.py
+++ b/tests/io/delta_lake/conftest.py
@@ -3,9 +3,11 @@
 import datetime
 
 import pandas as pd
+import pyarrow as pa
 import pytest
 
 deltalake = pytest.importorskip("deltalake")
+PYARROW_GE_13_0_0 = tuple(int(s) for s in pa.__version__.split(".") if s.isnumeric()) >= (13, 0, 0)
 
 
 @pytest.fixture(params=[None, "part_idx"])
@@ -25,9 +27,10 @@ def local_deltalake_table(request, tmp_path, partition_by) -> deltalake.DeltaTab
             "e": [datetime.datetime(2024, 2, 10), datetime.datetime(2024, 2, 11), datetime.datetime(2024, 2, 12)],
         }
     )
-    # Delta Lake casts timestamps to microsecond resolution on ingress, so we preemptively cast the Pandas DataFrame here
-    # to make equality assertions easier later.
-    base_df["e"] = base_df["e"].astype("datetime64[us]")
+    if PYARROW_GE_13_0_0:
+        # Delta Lake casts timestamps to microsecond resolution on ingress with later pyarrow versions, so we
+        # preemptively cast the Pandas DataFrame here to make equality assertions easier later.
+        base_df["e"] = base_df["e"].astype("datetime64[us]")
     dfs = []
     for part_idx in range(request.param):
         part_df = base_df.copy()
diff --git a/tests/io/delta_lake/test_table_read.py b/tests/io/delta_lake/test_table_read.py
index b3715fe3b6..fb1ad310d2 100644
--- a/tests/io/delta_lake/test_table_read.py
+++ b/tests/io/delta_lake/test_table_read.py
@@ -14,6 +14,7 @@
 
 PYARROW_LE_8_0_0 = tuple(int(s) for s in pa.__version__.split(".") if s.isnumeric()) < (8, 0, 0)
 pytestmark = pytest.mark.skipif(PYARROW_LE_8_0_0, reason="deltalake only supported if pyarrow >= 8.0.0")
+PYARROW_GE_13_0_0 = tuple(int(s) for s in pa.__version__.split(".") if s.isnumeric()) >= (13, 0, 0)
 
 
 def test_deltalake_read_basic(tmp_path):
@@ -28,8 +29,9 @@ def test_deltalake_read_basic(tmp_path):
     deltalake.write_deltalake(path, pd_df)
     df = daft.read_delta_lake(str(path))
     assert df.schema() == Schema.from_pyarrow_schema(deltalake.DeltaTable(path).schema().to_pyarrow())
-    # Delta Lake casts timestamps to microsecond resolution on ingress.
-    pd_df["c"] = pd_df["c"].astype("datetime64[us]")
+    if PYARROW_GE_13_0_0:
+        # Delta Lake casts timestamps to microsecond resolution on ingress with later pyarrow versions.
+        pd_df["c"] = pd_df["c"].astype("datetime64[us]")
     pd.testing.assert_frame_equal(df.to_pandas(), pd_df)