diff --git a/.changes/unreleased/Fixes-20241121-112638.yaml b/.changes/unreleased/Fixes-20241121-112638.yaml
new file mode 100644
index 00000000000..15a23ae8995
--- /dev/null
+++ b/.changes/unreleased/Fixes-20241121-112638.yaml
@@ -0,0 +1,6 @@
+kind: Fixes
+body: Make microbatch models skippable
+time: 2024-11-21T11:26:38.192345-05:00
+custom:
+  Author: michelleark
+  Issue: "11021"
diff --git a/core/dbt/task/run.py b/core/dbt/task/run.py
index 1b4be463e78..0c2888bb325 100644
--- a/core/dbt/task/run.py
+++ b/core/dbt/task/run.py
@@ -2,7 +2,7 @@
 import threading
 import time
 from copy import deepcopy
-from dataclasses import asdict, field
+from dataclasses import asdict
 from datetime import datetime
 from multiprocessing.pool import ThreadPool
 from typing import AbstractSet, Any, Dict, Iterable, List, Optional, Set, Tuple, Type
@@ -334,9 +334,12 @@ def execute(self, model, manifest):
 
 
 class MicrobatchModelRunner(ModelRunner):
-    batch_idx: Optional[int] = None
-    batches: Dict[int, BatchType] = field(default_factory=dict)
-    relation_exists: bool = False
+    def __init__(self, config, adapter, node, node_index: int, num_nodes: int):
+        super().__init__(config, adapter, node, node_index, num_nodes)
+
+        self.batch_idx: Optional[int] = None
+        self.batches: Dict[int, BatchType] = {}
+        self.relation_exists: bool = False
 
     def set_batch_idx(self, batch_idx: int) -> None:
         self.batch_idx = batch_idx
@@ -704,8 +707,11 @@ def handle_microbatch_model(
         runner: MicrobatchModelRunner,
         pool: ThreadPool,
     ) -> RunResult:
-        # Initial run computes batch metadata
+        # Initial run computes batch metadata, unless model is skipped
         result = self.call_runner(runner)
+        if result.status == RunStatus.Skipped:
+            return result
+
         batch_results: List[RunResult] = []
 
         # Execute batches serially until a relation exists, at which point future batches are run in parallel
diff --git a/tests/functional/microbatch/test_microbatch.py b/tests/functional/microbatch/test_microbatch.py
index c9b9db2ff4e..ddac8959a5a 100644
--- a/tests/functional/microbatch/test_microbatch.py
+++ b/tests/functional/microbatch/test_microbatch.py
@@ -33,6 +33,12 @@
 select 3 as id, TIMESTAMP '2020-01-03 00:00:00-0' as event_time
 """
 
+input_model_invalid_sql = """
+{{ config(materialized='table', event_time='event_time') }}
+
+select invalid as event_time
+"""
+
 input_model_without_event_time_sql = """
 {{ config(materialized='table') }}
 
@@ -835,6 +841,24 @@ def test_microbatch(
             assert len(catch_aw.caught_events) == 1
 
 
+class TestMicrobatchModelSkipped(BaseMicrobatchTest):
+    @pytest.fixture(scope="class")
+    def models(self):
+        return {
+            "input_model.sql": input_model_invalid_sql,
+            "microbatch_model.sql": microbatch_model_sql,
+        }
+
+    def test_microbatch_model_skipped(self, project) -> None:
+        run_dbt(["run"], expect_pass=False)
+
+        run_results = get_artifact(project.project_root, "target", "run_results.json")
+
+        microbatch_result = run_results["results"][1]
+        assert microbatch_result["status"] == "skipped"
+        assert microbatch_result["batch_results"] is None
+
+
 class TestMicrobatchCanRunParallelOrSequential(BaseMicrobatchTest):
     @pytest.fixture
     def batch_exc_catcher(self) -> EventCatcher: