diff --git a/changes/4189.bugfix.md b/changes/4189.bugfix.md
new file mode 100644
index 0000000000..76ef7e7a5e
--- /dev/null
+++ b/changes/4189.bugfix.md
@@ -0,0 +1 @@
+Allow `Group.require_array` to accept a `ZDType` for `dtype`, matching the other array creation methods. Previously an existing array could only be required with a string or NumPy dtype.
diff --git a/src/zarr/core/group.py b/src/zarr/core/group.py
index 65f7767a29..548f2141d2 100644
--- a/src/zarr/core/group.py
+++ b/src/zarr/core/group.py
@@ -10,7 +10,6 @@
 from typing import TYPE_CHECKING, Literal, assert_never, cast, overload
 
 import numpy as np
-import numpy.typing as npt
 
 import zarr.api.asynchronous as async_api
 from zarr.abc.metadata import Metadata
@@ -46,6 +45,7 @@
     parse_shapelike,
 )
 from zarr.core.config import config
+from zarr.core.dtype import parse_data_type
 from zarr.core.metadata import ArrayV2Metadata, ArrayV3Metadata
 from zarr.core.metadata.io import save_metadata
 from zarr.core.sync import SyncMixin, sync
@@ -1225,7 +1225,7 @@ async def require_array(
         name: str,
         *,
         shape: ShapeLike,
-        dtype: npt.DTypeLike | None = None,
+        dtype: ZDTypeLike | None = None,
         exact: bool = False,
         **kwargs: Any,
     ) -> AnyAsyncArray:
@@ -1239,8 +1239,9 @@ async def require_array(
             Array name.
         shape : int or tuple of ints
             Array shape.
-        dtype : str or dtype, optional
-            NumPy dtype.
+        dtype : ZDTypeLike, optional
+            The data type of the array, given as a string, a NumPy dtype, or a
+            Zarr data type.
         exact : bool, optional
             If True, require `dtype` to match exactly. If false, require
             `dtype` can be cast from array dtype.
@@ -1258,7 +1259,11 @@ async def require_array(
             if shape != ds.shape:
                 raise TypeError(f"Incompatible shape ({ds.shape} vs {shape})")
 
-            dtype = np.dtype(dtype)
+            # `np.dtype(None)` used to resolve to float64 here; keep that default.
+            dtype = parse_data_type(
+                "float64" if dtype is None else dtype,
+                zarr_format=self.metadata.zarr_format,
+            ).to_native_dtype()
             if exact:
                 if ds.dtype != dtype:
                     raise TypeError(f"Incompatible dtype ({ds.dtype} vs {dtype})")
diff --git a/tests/test_group.py b/tests/test_group.py
index 29377a5392..f7f2333ef5 100644
--- a/tests/test_group.py
+++ b/tests/test_group.py
@@ -24,6 +24,7 @@
 from zarr.core._info import GroupInfo
 from zarr.core.buffer import default_buffer_prototype
 from zarr.core.config import config as zarr_config
+from zarr.core.dtype import Float64, Int32
 from zarr.core.dtype.common import unpack_dtype_json
 from zarr.core.dtype.npy.int import UInt8
 from zarr.core.group import (
@@ -61,6 +62,7 @@
 
     from zarr.core.buffer.core import Buffer
     from zarr.core.common import JSON, ZarrFormat
+    from zarr.core.dtype import ZDType, ZDTypeLike
 
 
 @pytest.fixture(params=["local", "memory", "zip"])
@@ -1439,6 +1441,29 @@ async def test_require_array(store: Store, zarr_format: ZarrFormat) -> None:
         await root.require_array("bar", shape=(10,), dtype="int8")
 
 
+@pytest.mark.parametrize(
+    ("dtype", "expected"),
+    [
+        (Int32(), Int32()),
+        (np.dtype("int32"), Int32()),
+        ("int32", Int32()),
+        (None, Float64()),
+    ],
+    ids=["zdtype", "numpy", "str", "none"],
+)
+async def test_require_array_zdtype(
+    store: Store, zarr_format: ZarrFormat, dtype: ZDTypeLike | None, expected: ZDType[Any, Any]
+) -> None:
+    """An existing array can be required with a ZDType, as well as a string, a NumPy dtype,
+    or None. See https://github.com/zarr-developers/zarr-python/issues/3377
+    """
+    root = await AsyncGroup.from_store(store=store, zarr_format=zarr_format)
+    await root.create_array("foo", shape=(10,), dtype=expected)
+
+    foo = await root.require_array("foo", shape=(10,), dtype=dtype, exact=True)
+    assert foo._zdtype == expected
+
+
 @pytest.mark.parametrize("consolidate", [True, False])
 async def test_members_name(store: Store, consolidate: bool, zarr_format: ZarrFormat):
     group = Group.from_store(store=store, zarr_format=zarr_format)