diff --git a/S3_cli_command.sh b/AWS_S3_CLI_command.sh
similarity index 100%
rename from S3_cli_command.sh
rename to AWS_S3_CLI_command.sh
diff --git a/AWS_lambda_function.py b/AWS_lambda_function.py
new file mode 100644
index 0000000..ec669ca
--- /dev/null
+++ b/AWS_lambda_function.py
@@ -0,0 +1,72 @@
+"""
+aws Lambda Function to process JSON data stored in an S3 bucket,
+transform it into a Pandas DataFrame, normalize the DataFrame, and write
+the resulting DataFrame to a Parquet file stored in another S3 bucket,
+optionally registering it as a table in AWS Glue catalog.
+"""
+
+import urllib.parse
+import os
+
+import awswrangler as wr
+import pandas as pd
+
+os_input_s3_cleansed_layer = os.environ['s3_cleansed_layer']
+os_input_glue_catalog_db_name = os.environ['glue_catalog_db_name']
+os_input_glue_catalog_table_name = os.environ['glue_catalog_table_name']
+os_input_write_data_operation = os.environ['write_data_operation']
+
+
+def lambda_handler(event, context):
+    """
+    Lambda function to process JSON data stored in an S3 bucket, transform it into a Pandas DataFrame,
+    normalize the DataFrame, and write the resulting DataFrame to a Parquet file stored in another S3 bucket,
+    optionally registering it as a table in AWS Glue catalog.
+
+    Parameters:
+    - event (dict): A dictionary containing information about the S3 event that triggered the Lambda function.
+                    Typically includes details about the S3 bucket and object.
+    - context (LambdaContext): An object providing runtime information about the Lambda function invocation.
+
+    Returns:
+    - dict: A dictionary containing the response from the AWS Data Wrangler write operation.
+
+    Raises:
+    - Exception: If there is an error processing the S3 object or writing to S3.
+                 This exception is raised to trigger AWS Lambda's error handling.
+
+    Notes:
+    - This Lambda function expects JSON data stored in the specified S3 bucket, reads it into a Pandas DataFrame,
+      extracts required columns, and writes the resulting DataFrame to another S3 bucket in Parquet format.
+    - It optionally registers the Parquet file as a table in the specified AWS Glue catalog database.
+    - Make sure that the required environment variables (s3_cleansed_layer, glue_catalog_db_name,
+      glue_catalog_table_name, write_data_operation) are properly set before invoking this Lambda function.
+    """
+    # Get the object from the event & show its content type -->
+    # getting the bucket name & key path to the object
+    bucket = event['Records'][0]['s3']['bucket']['name']
+    key = urllib.parse.unquote_plus(event['Records'][0]['s3']['object']['key'], encoding='utf-8')
+    try:
+
+        # Creating DF from the content
+        df_raw = wr.s3.read_json('s3://{}/{}'.format(bucket, key))
+
+        # Extract the required column of items:
+        df_step_1 = pd.json_normalize(df_raw['items'])
+
+        # Write to S3
+        wr_response = wr.s3.to_parquet(
+            df=df_step_1,
+            path=os_input_s3_cleansed_layer,
+            dataset=True,
+            database=os_input_glue_catalog_db_name,
+            table=os_input_glue_catalog_table_name,
+            mode=os_input_write_data_operation
+        )
+
+        return wr_response
+
+    except Exception as e:
+        print(e)
+        print('Error getting object {} from the bucket {}. Make sure they exist & your bucket is in the same region as this function.'.format(key, bucket))
+        raise e