diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index afb2f91f65ccd..7af5956cd768b 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -500,6 +500,7 @@ Datetimelike
 - Bug in :meth:`DatetimeIndex.is_year_start` and :meth:`DatetimeIndex.is_quarter_start` does not raise on Custom business days frequencies bigger then "1C" (:issue:`58664`)
 - Bug in :meth:`DatetimeIndex.is_year_start` and :meth:`DatetimeIndex.is_quarter_start` returning ``False`` on double-digit frequencies (:issue:`58523`)
 - Bug in :meth:`DatetimeIndex.union` when ``unit`` was non-nanosecond (:issue:`59036`)
+- Bug in :meth:`Series.dt.microsecond` with:class:`ArrowDtype` returning incorrect values. (:issue:`59154`)
 - Bug in setting scalar values with mismatched resolution into arrays with non-nanosecond ``datetime64``, ``timedelta64`` or :class:`DatetimeTZDtype` incorrectly truncating those scalars (:issue:`56410`)
 
 Timedelta
diff --git a/pandas/core/arrays/arrow/array.py b/pandas/core/arrays/arrow/array.py
index 4ff7553af2b69..1ba6ad3f8cabd 100644
--- a/pandas/core/arrays/arrow/array.py
+++ b/pandas/core/arrays/arrow/array.py
@@ -2794,7 +2794,14 @@ def _dt_days_in_month(self) -> Self:
 
     @property
     def _dt_microsecond(self) -> Self:
-        return type(self)(pc.microsecond(self._pa_array))
+        us = pc.microsecond(self._pa_array)
+        ms_us = pc.multiply(
+            pc.millisecond(self._pa_array), pa.scalar(1000, type=us.type)
+        )
+        s_us = pc.multiply(
+            pc.second(self._pa_array), pa.scalar(1_000_000, type=us.type)
+        )
+        return type(self)(pc.add(pc.add(ms_us, s_us), us))
 
     @property
     def _dt_minute(self) -> Self:
diff --git a/pandas/tests/extension/test_arrow.py b/pandas/tests/extension/test_arrow.py
index f2e9d2321f33e..c7840cdbf3da9 100644
--- a/pandas/tests/extension/test_arrow.py
+++ b/pandas/tests/extension/test_arrow.py
@@ -3536,3 +3536,13 @@ 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_microsecond():
+    series = pd.Series(
+        [946684800000000000, 946684800015000000, 946684800030000000],
+        dtype=ArrowDtype(pa.timestamp("ns")),
+    )
+    result = series.dt.microsecond
+    expected = pd.Series([0, 15000, 30000], dtype="int64[pyarrow]")
+    tm.assert_series_equal(result, expected)