diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 83638ce87f7ac..010d4a31b864d 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -651,6 +651,7 @@ Conversion
 - Bug in :meth:`DataFrame.update` bool dtype being converted to object (:issue:`55509`)
 - Bug in :meth:`Series.astype` might modify read-only array inplace when casting to a string dtype (:issue:`57212`)
 - Bug in :meth:`Series.reindex` not maintaining ``float32`` type when a ``reindex`` introduces a missing value (:issue:`45857`)
+- Bug in :meth: 'Series.convert_dtype' strips the timezone on an already Timezone aware pyarrow timestamp dtype (:issue:'60237')
 
 Strings
 ^^^^^^^
diff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py
index 1dd1b12d6ae95..5a88591a144b8 100644
--- a/pandas/core/dtypes/dtypes.py
+++ b/pandas/core/dtypes/dtypes.py
@@ -2280,7 +2280,8 @@ def numpy_dtype(self) -> np.dtype:
             # regardless of the pyarrow timestamp units.
             # This can be removed if/when pyarrow addresses it:
             # https://github.com/apache/arrow/issues/34462
-            return np.dtype(f"datetime64[{self.pyarrow_dtype.unit}]")
+            if self.pyarrow_dtype.tz is None:
+                return np.dtype(f"datetime64[{self.pyarrow_dtype.unit}]")
         if pa.types.is_duration(self.pyarrow_dtype):
             # pa.duration(unit).to_pandas_dtype() returns ns units
             # regardless of the pyarrow duration units
diff --git a/pandas/tests/extension/test_arrow.py b/pandas/tests/extension/test_arrow.py
index c6ac6368f2770..55cec8662a465 100644
--- a/pandas/tests/extension/test_arrow.py
+++ b/pandas/tests/extension/test_arrow.py
@@ -3505,3 +3505,14 @@ def test_map_numeric_na_action():
     result = ser.map(lambda x: 42, na_action="ignore")
     expected = pd.Series([42.0, 42.0, np.nan], dtype="float64")
     tm.assert_series_equal(result, expected)
+
+
+def test_convert_dtypes_timezone_series():
+    # GH#60237
+    ser = pd.Series(
+        pd.date_range(start="2020-01-01", periods=5, freq="h", tz="UTC"),
+        dtype="timestamp[ns, tz=UTC][pyarrow]",
+    )
+    expected = ser
+    result = ser.convert_dtypes(dtype_backend="pyarrow")
+    tm.assert_series_equal(result, expected)