diff --git a/python/pyarrow/array.pxi b/python/pyarrow/array.pxi
index e47327ff2d4..e35717d7424 100644
--- a/python/pyarrow/array.pxi
+++ b/python/pyarrow/array.pxi
@@ -903,12 +903,10 @@ cdef class Array(_PandasConvertible):
                                               self, &out))
         result = pandas_api.series(wrap_array_output(out), name=self._name)
 
-        if isinstance(self.type, TimestampType):
-            tz = self.type.tz
-            if tz is not None:
-                tz = string_to_tzinfo(tz)
-                result = (result.dt.tz_localize('utc')
-                          .dt.tz_convert(tz))
+        if isinstance(self.type, TimestampType) and self.type.tz is not None:
+            from pyarrow.pandas_compat import make_tz_aware
+
+            result = make_tz_aware(result, self.type.tz)
 
         return result
 
diff --git a/python/pyarrow/pandas_compat.py b/python/pyarrow/pandas_compat.py
index 4b7e2e02987..900711ab6bd 100644
--- a/python/pyarrow/pandas_compat.py
+++ b/python/pyarrow/pandas_compat.py
@@ -1046,3 +1046,17 @@ def _add_any_metadata(table, pandas_metadata):
         return pa.Table.from_arrays(columns, schema=pa.schema(fields))
     else:
         return table
+
+
+# ----------------------------------------------------------------------
+# Helper functions used in lib
+
+
+def make_tz_aware(series, tz):
+    """
+    Make a datetime64 Series timezone-aware for the given tz
+    """
+    tz = pa.lib.string_to_tzinfo(tz)
+    series = (series.dt.tz_localize('utc')
+                    .dt.tz_convert(tz))
+    return series
diff --git a/python/pyarrow/table.pxi b/python/pyarrow/table.pxi
index a09766fd4b7..086c4f45011 100644
--- a/python/pyarrow/table.pxi
+++ b/python/pyarrow/table.pxi
@@ -163,7 +163,14 @@ cdef class ChunkedArray(_PandasConvertible):
                 self.sp_chunked_array,
                 self, &out))
 
-        return pandas_api.series(wrap_array_output(out), name=self._name)
+        result = pandas_api.series(wrap_array_output(out), name=self._name)
+
+        if isinstance(self.type, TimestampType) and self.type.tz is not None:
+            from pyarrow.pandas_compat import make_tz_aware
+
+            result = make_tz_aware(result, self.type.tz)
+
+        return result
 
     def __array__(self, dtype=None):
         values = self.to_pandas().values
diff --git a/python/pyarrow/tests/test_array.py b/python/pyarrow/tests/test_array.py
index 9aa8a7c8b48..91ca247aa27 100644
--- a/python/pyarrow/tests/test_array.py
+++ b/python/pyarrow/tests/test_array.py
@@ -1786,3 +1786,6 @@ def test_to_pandas_timezone():
     arr = pa.array([1, 2, 3], type=pa.timestamp('s', tz='Europe/Brussels'))
     s = arr.to_pandas()
     assert s.dt.tz is not None
+    arr = pa.chunked_array([arr])
+    s = arr.to_pandas()
+    assert s.dt.tz is not None
diff --git a/python/pyarrow/tests/test_table.py b/python/pyarrow/tests/test_table.py
index f9b2092ce07..434ec8029c1 100644
--- a/python/pyarrow/tests/test_table.py
+++ b/python/pyarrow/tests/test_table.py
@@ -187,15 +187,19 @@ def test_chunked_array_pickle(data, typ):
 
 @pytest.mark.pandas
 def test_chunked_array_to_pandas():
+    import pandas as pd
+
     data = [
         pa.array([-10, -5, 0, 5, 10])
     ]
     table = pa.table(data, names=['a'])
     col = table.column(0)
     assert isinstance(col, pa.ChunkedArray)
-    array = col.to_pandas()
-    assert array.shape == (5,)
-    assert array[0] == -10
+    series = col.to_pandas()
+    assert isinstance(series, pd.Series)
+    assert series.shape == (5,)
+    assert series[0] == -10
+    assert series.name == 'a'
 
 
 @pytest.mark.pandas