add delta lake to iceberg blueprint and IT

python/src/main/python/job-builder-util-transforms/provider_listing_template.yaml

@@ -4,4 +4,5 @@
       - https://storage.googleapis.com/<package_path>
   transforms:
     CopyFilesToGCS: "copy_files_to_gcs.CopyFilesToGCS"
-    ReadFromDeltaLake: "read_from_delta_lake.ReadFromDeltaLake"
+    ReadFromDeltaLake: "read_from_delta_lake.ReadFromDeltaLake"
+    WriteToLakehouse: "write_to_lakehouse.WriteToLakehouse"

python/src/main/python/job-builder-util-transforms/pyproject.toml

@@ -6,6 +6,7 @@ authors = ["Google Cloud Platform"]
 packages = [
     { include = "copy_files_to_gcs.py" },
     { include = "read_from_delta_lake.py" },
+    { include = "write_to_lakehouse.py" },
 ]
 
 [tool.poetry.dependencies]

python/src/main/python/job-builder-util-transforms/write_to_lakehouse.py

@@ -0,0 +1,72 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Module containing transforms to write data to Lakehouse tables."""
+
+from typing import Iterable, Mapping, Optional
+from apache_beam.transforms import PTransform
+from apache_beam.yaml.yaml_io import write_to_iceberg
+
+
+class WriteToLakehouse(PTransform):
+  """A PTransform that writes data to a Lakehouse table.
+
+  Currently, it wraps the Apache Iceberg sink.
+  """
+
+  def __init__(
+      self,
+      table: str,
+      catalog_name: Optional[str] = None,
+      catalog_properties: Optional[Mapping[str, str]] = None,
+      config_properties: Optional[Mapping[str, str]] = None,
+      partition_fields: Optional[Iterable[str]] = None,
+      table_properties: Optional[Mapping[str, str]] = None,
+      triggering_frequency_seconds: Optional[int] = None,
+      keep: Optional[Iterable[str]] = None,
+      drop: Optional[Iterable[str]] = None,
+      only: Optional[str] = None,
+      distribution_mode: Optional[str] = None,
+      autosharding: Optional[bool] = None,
+  ):
+    super().__init__()
+    self.table = table
+    self.catalog_name = catalog_name
+    self.catalog_properties = catalog_properties
+    self.config_properties = config_properties
+    self.partition_fields = partition_fields
+    self.table_properties = table_properties
+    self.triggering_frequency_seconds = triggering_frequency_seconds
+    self.keep = keep
+    self.drop = drop
+    self.only = only
+    self.distribution_mode = distribution_mode
+    self.autosharding = autosharding
+
+  def expand(self, pcoll):
+    """Expands the WriteToLakehouse transform."""
+    return pcoll | write_to_iceberg(
+        table=self.table,
+        catalog_name=self.catalog_name,
+        catalog_properties=self.catalog_properties,
+        config_properties=self.config_properties,
+        partition_fields=self.partition_fields,
+        table_properties=self.table_properties,
+        triggering_frequency_seconds=self.triggering_frequency_seconds,
+        keep=self.keep,
+        drop=self.drop,
+        only=self.only,
+        distribution_mode=self.distribution_mode,
+        autosharding=self.autosharding,
+    )

python/src/test/python/job-builder-util-transforms/write_to_lakehouse_test.py

@@ -0,0 +1,75 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+from unittest.mock import MagicMock, patch
+from write_to_lakehouse import WriteToLakehouse
+
+
+class WriteToLakehouseTest(unittest.TestCase):
+
+  @patch("write_to_lakehouse.write_to_iceberg")
+  def test_write_to_lakehouse(self, mock_write_to_iceberg):
+    mock_transform = MagicMock()
+    mock_write_to_iceberg.return_value = mock_transform
+
+    table = "lakehouse_catalog.dataset.table"
+    catalog_name = "lakehouse_catalog"
+    catalog_properties = {"type": "hadoop", "warehouse": "gs://bucket/warehouse"}
+    config_properties = {"fs.gs.impl": "com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystem"}
+    partition_fields = ["day(ts)", "category"]
+    table_properties = {"commit.retry.num-retries": "2"}
+    triggering_frequency_seconds = 60
+    keep = ["field1", "field2"]
+    drop = ["field3"]
+    only = "field4"
+    distribution_mode = "hash"
+    autosharding = True
+
+    transform = WriteToLakehouse(
+        table=table,
+        catalog_name=catalog_name,
+        catalog_properties=catalog_properties,
+        config_properties=config_properties,
+        partition_fields=partition_fields,
+        table_properties=table_properties,
+        triggering_frequency_seconds=triggering_frequency_seconds,
+        keep=keep,
+        drop=drop,
+        only=only,
+        distribution_mode=distribution_mode,
+        autosharding=autosharding,
+    )
+
+    pcoll = MagicMock()
+    transform.expand(pcoll)
+
+    mock_write_to_iceberg.assert_called_once_with(
+        table=table,
+        catalog_name=catalog_name,
+        catalog_properties=catalog_properties,
+        config_properties=config_properties,
+        partition_fields=partition_fields,
+        table_properties=table_properties,
+        triggering_frequency_seconds=triggering_frequency_seconds,
+        keep=keep,
+        drop=drop,
+        only=only,
+        distribution_mode=distribution_mode,
+        autosharding=autosharding,
+    )
+
+
+if __name__ == "__main__":
+  unittest.main()