diff --git a/src/test/java/com/snowflake/kafka/connector/internal/streaming/TopicPartitionChannelIT.java b/src/test/java/com/snowflake/kafka/connector/internal/streaming/TopicPartitionChannelIT.java
index 99bf7f30a..f2c6cf0b1 100644
--- a/src/test/java/com/snowflake/kafka/connector/internal/streaming/TopicPartitionChannelIT.java
+++ b/src/test/java/com/snowflake/kafka/connector/internal/streaming/TopicPartitionChannelIT.java
@@ -18,6 +18,9 @@
 import net.snowflake.ingest.streaming.OpenChannelRequest;
 import net.snowflake.ingest.streaming.SnowflakeStreamingIngestClient;
 import org.apache.kafka.common.TopicPartition;
+import org.apache.kafka.connect.data.Schema;
+import org.apache.kafka.connect.data.SchemaAndValue;
+import org.apache.kafka.connect.json.JsonConverter;
 import org.apache.kafka.connect.sink.SinkRecord;
 import org.junit.After;
 import org.junit.Assert;
@@ -485,4 +488,65 @@ public void testSimpleInsertRowsFailureWithArrowBDECFormat() throws Exception {
     service.insert(records);
     service.closeAll();
   }
+
+  @Test
+  public void testPartialBatchChannelInvalidationIngestion_schematization() throws Exception {
+    Map<String, String> config = TestUtils.getConfForStreaming();
+    config.put(SnowflakeSinkConnectorConfig.BUFFER_COUNT_RECORDS, "500"); // we want to flush on record
+    config.put(SnowflakeSinkConnectorConfig.BUFFER_FLUSH_TIME_SEC, "500000");
+    config.put(SnowflakeSinkConnectorConfig.BUFFER_SIZE_BYTES, "500000");
+    config.put(SnowflakeSinkConnectorConfig.ENABLE_SCHEMATIZATION_CONFIG, "true"); // using schematization to invalidate
+
+    // setup
+    InMemorySinkTaskContext inMemorySinkTaskContext =
+        new InMemorySinkTaskContext(Collections.singleton(topicPartition));
+    SnowflakeSinkService service =
+        SnowflakeSinkServiceFactory.builder(conn, IngestionMethodConfig.SNOWPIPE_STREAMING, config)
+            .setRecordNumber(1)
+            .setErrorReporter(new InMemoryKafkaRecordErrorReporter())
+            .setSinkTaskContext(inMemorySinkTaskContext)
+            .addTask(testTableName, topicPartition)
+            .build();
+
+    final long firstBatchCount = 18;
+    final long secondBatchCount = 500;
+
+    // create 18 blank records that do not kick off schematization
+    JsonConverter converter = new JsonConverter();
+    HashMap<String, String> converterConfig = new HashMap<>();
+    converterConfig.put("schemas.enable", "false");
+    converter.configure(converterConfig, false);
+    SchemaAndValue schemaInputValue = converter.toConnectData("test", null);
+
+    List<SinkRecord> firstBatch = new ArrayList<>();
+    for (int i = 0; i < firstBatchCount; i++) {
+      firstBatch.add(new SinkRecord(
+          topic,
+          PARTITION,
+          Schema.STRING_SCHEMA,
+          "test",
+          schemaInputValue.schema(),
+          schemaInputValue.value(),
+          i));
+    }
+
+    service.insert(firstBatch);
+
+    // send batch with 500, should kick off a record based flush and schematization on record 19, which will fail the batches
+    List<SinkRecord> secondBatch =
+        TestUtils.createNativeJsonSinkRecords(firstBatchCount, secondBatchCount, topic, PARTITION);
+    service.insert(secondBatch);
+
+    // resend batch 1 and 2 because 2 failed for schematization
+    service.insert(firstBatch);
+    service.insert(secondBatch);
+
+    // ensure all data was ingested
+    TestUtils.assertWithRetry(
+        () -> service.getOffset(new TopicPartition(topic, PARTITION)) == firstBatchCount + secondBatchCount, 20, 5);
+    assert TestUtils.tableSize(testTableName) == firstBatchCount + secondBatchCount
+        : "expected: " + firstBatchCount + secondBatchCount + " actual: " + TestUtils.tableSize(testTableName);
+
+    service.closeAll();
+  }
 }