diff --git a/CHANGELOG-dguan2-STAR-9183.adoc b/CHANGELOG-dguan2-STAR-9183.adoc
new file mode 100644
index 0000000..505f953
--- /dev/null
+++ b/CHANGELOG-dguan2-STAR-9183.adoc
@@ -0,0 +1 @@
+* ({uri-jira}/STAR-9183[STAR-9183]) - Add nullify column option to Dumpty
\ No newline at end of file
diff --git a/config.yaml.example b/config.yaml.example
index 89567f2..2f80ea3 100644
--- a/config.yaml.example
+++ b/config.yaml.example
@@ -76,7 +76,7 @@ log_file: {{EXTRACT_LOG_FILE}}
 
 # Source database schema name
 schema: dbo
-
+empty_columns: "patient.ssn,provider.dea"
 # Tables to extract from above schema
 tables: 
   - REPORTS
@@ -85,4 +85,4 @@ views:
   - name: VIEW_MAT
     materialized: true
   - name: VIEW_SQL
-    file: vv_Example.sql
\ No newline at end of file
+    file: vv_Example.sql
diff --git a/src/dumpty/config.py b/src/dumpty/config.py
index 9fbfda5..3881ac0 100644
--- a/src/dumpty/config.py
+++ b/src/dumpty/config.py
@@ -60,6 +60,7 @@ class Config(YAMLWizard):
     create_views_workers: int = 8
     drop_dataset: bool = False
     normalize_schema: bool = True
+    empty_columns: str = None
     last_successful_run: str = None
     extract: str = None
     tables_query: str = None
diff --git a/src/dumpty/main.py b/src/dumpty/main.py
index e20ce72..51c9471 100644
--- a/src/dumpty/main.py
+++ b/src/dumpty/main.py
@@ -119,6 +119,13 @@ def config_from_args(argv) -> Config:
         help="Local path or gs:// URI to store extracted data",
     )
 
+    parser.add_argument(
+        "--empty_columns",
+        type=str,
+        default=None,
+        help="Empty the values of table columns (e.g. table1_name.field1_name,table2_name.field2_name)",
+    )
+
     parser.add_argument(
         "dataset",
         type=str,
@@ -241,6 +248,7 @@ def main(args=None):
     logger.info("config.target_dataset_location: %s", config.target_dataset_location)
     logger.info("config.drop_dataset: %s", config.drop_dataset)
     logger.info("config.normalize_schema: %s", config.normalize_schema)
+    logger.info("config.empty_columns: %s", config.empty_columns)
     logger.info("config.extract: %s", config.extract)
     logger.info("config.last_successful_run: %s", config.last_successful_run)
     logger.info("config.tables_query: %s", config.tables_query)
diff --git a/src/dumpty/pipeline.py b/src/dumpty/pipeline.py
index c2f5f47..053a54f 100644
--- a/src/dumpty/pipeline.py
+++ b/src/dumpty/pipeline.py
@@ -171,6 +171,20 @@ def __exit__(self, exc_type, exc_val, exc_tb):
         # sleep(36000)
         self._spark_session.stop()
 
+    @staticmethod
+    def empty_cols(df: DataFrame, table_name: str, drop_cols: str) -> DataFrame:
+        drop_col_names: List[str] = []
+        for col_name in drop_cols.split(','):
+            if col_name.rsplit('.')[0].lower() == table_name.lower():
+                drop_col_names.append(col_name.rsplit('.')[-1])
+                # Dataframe drop doesn't work. When it saves the data, the columns still exists. e.g. df.drop(col_name.rsplit('.')[-1])
+                logger.info(
+                    f"Table {table_name} - Drop column: {col_name.rsplit('.')[-1]}")
+        if len(drop_col_names) > 0:
+            return df.select([c for c in df.columns if c not in drop_col_names])
+        else:
+            return df
+
     @staticmethod
     def normalize_df(df: DataFrame) -> DataFrame:
         return df.select([col(x).alias(normalize_str(x)) for x in df.columns])
@@ -694,6 +708,9 @@ def _extract(self, extract: Extract, uri: str) -> str:
             # Normalize column names?
             df = self.normalize_df(df)
 
+        if self.config.empty_columns is not None:
+            df = self.empty_cols(df, extract.name, self.config.empty_columns)
+
         session.sparkContext.setLocalProperty("callSite.short", n_table_name)
         df.write.save(f"{uri}/{n_table_name}", format=self.config.spark.format, mode="overwrite",
                       timestampFormat=self.config.spark.timestamp_format, compression=self.config.spark.compression)
@@ -773,7 +790,7 @@ def load(self, extract: Extract) -> Extract:
 
         # Load into BigQuery
         if self.config.target_dataset is not None:
-            if self.config.schemaonly == False and extract.rows > 0:
+            if self.config.schemaonly == False:
                 # Load from GCS into BQ
                 bq_rows: int = 0
                 bq_bytes: int = 0