@@ -584,7 +584,9 @@ def _normalize_slice(object arrow_obj, slice key):
     start, stop, step = key.indices(n)
 
     if step != 1:
-        indices = np.arange(start, stop, step)
+        indices = list(range(start, stop, step))
+        if len(indices) == 0:
+            return arrow_obj.slice(0, 0)
         return arrow_obj.take(indices)
     else:
         length = max(stop - start, 0)
 
@@ -503,15 +503,14 @@ def test_array_slice():
                 assert res.to_numpy().tolist() == expected
 
 
-@pytest.mark.numpy
 def test_array_slice_negative_step():
     # ARROW-2714
-    np_arr = np.arange(20)
-    arr = pa.array(np_arr)
+    values = list(range(20))
+    arr = pa.array(values)
     chunked_arr = pa.chunked_array([arr])
 
     cases = [
-        slice(None, None, -1),
+        slice(None, None, -1),  # GH-46606
         slice(None, 6, -2),
         slice(10, 6, -2),
         slice(8, None, -2),
@@ -525,15 +524,15 @@ def test_array_slice_negative_step():
 
     for case in cases:
         result = arr[case]
-        expected = pa.array(np_arr[case])
+        expected = pa.array(values[case], type=arr.type)
         assert result.equals(expected)
 
         result = pa.record_batch([arr], names=['f0'])[case]
         expected = pa.record_batch([expected], names=['f0'])
         assert result.equals(expected)
 
         result = chunked_arr[case]
-        expected = pa.chunked_array([np_arr[case]])
+        expected = pa.chunked_array([values[case]], type=arr.type)
         assert result.equals(expected)