diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py
index 2b8ed3c97d026..24ac7c040a45d 100644
--- a/pandas/core/window/rolling.py
+++ b/pandas/core/window/rolling.py
@@ -2513,8 +2513,9 @@ def _get_window_indexer(self) -> GroupbyIndexer:
     def _validate_monotonic(self):
         """
         Validate that on is monotonic;
-        in this case we have to check only for nans, because
-        monotonicity was already validated at a higher level.
         """
-        if self._on.hasnans:
+        if (
+            not (self._on.is_monotonic_increasing or self._on.is_monotonic_decreasing)
+            or self._on.hasnans
+        ):
             self._raise_monotonic_error()
diff --git a/pandas/tests/window/test_rolling.py b/pandas/tests/window/test_rolling.py
index d58eeaa7cbcb1..0391dc56c5791 100644
--- a/pandas/tests/window/test_rolling.py
+++ b/pandas/tests/window/test_rolling.py
@@ -1417,6 +1417,17 @@ def test_groupby_rolling_nan_included():
     tm.assert_frame_equal(result, expected)
 
 
+def test_groupby_rolling_non_monotonic():
+    # GH 43909
+    shuffled = [3, 0, 1, 2]
+    sec = 1_000_000_000
+    df = DataFrame(
+        [{"t": Timestamp(2 * x * sec), "x": x + 1, "c": 42} for x in shuffled]
+    )
+    with pytest.raises(ValueError, match=r".* must be monotonic"):
+        df.groupby("c").rolling(on="t", window="3s")
+
+
 @pytest.mark.parametrize("method", ["skew", "kurt"])
 def test_rolling_skew_kurt_numerical_stability(method):
     # GH#6929