### Description

Airflow provides the Amazon DynamoDB to Amazon S3 below.  
https://airflow.apache.org/docs/apache-airflow-providers-amazon/stable/operators/transfer/dynamodb_to_s3.html

Most of Data Engineer build their "export DDB data to s3" pipeline using "within the point in time recovery window".   
https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/dynamodb.html#DynamoDB.Client.export_table_to_point_in_time

I appreciate if airflow has this function as a native function.  

### Use case/motivation

My daily batch job exports its data with pitr option. All of tasks is written by apache-airflow-providers-amazon except "export_table_to_point_in_time" task. 
"export_table_to_point_in_time" task only used the python operator. I expect I can unify the task as apache-airflow-providers-amazon library. 

### Related issues

_No response_

### Are you willing to submit a PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

waiter = boto3.client("s3").get_waiter("bucket_exists")
    waiter.wait(Bucket=s3_bucket_name)
@task(trigger_rule=TriggerRule.ALL_DONE)
def delete_dynamodb_table(table_name: str):
    boto3.resource("dynamodb").Table(table_name).delete()
    boto3.client("dynamodb").get_waiter("table_not_exists").wait(
        TableName=table_name, WaiterConfig={"Delay": 10, "MaxAttempts": 10}
    )
with DAG(
    dag_id=DAG_ID,
    schedule="@once",
    start_date=datetime(2021, 1, 1),
    catchup=False,
    tags=["example"],
) as dag:
    test_context = sys_test_context_task()
    env_id = test_context[ENV_ID_KEY]
    table_name = f"{env_id}-dynamodb-table"
    bucket_name = f"{env_id}-dynamodb-bucket"
    create_table = set_up_table(table_name=table_name)
    create_bucket = S3CreateBucketOperator(task_id="create_bucket", bucket_name=bucket_name)
    
    backup_db = DynamoDBToS3Operator(
        task_id="backup_db",
        dynamodb_table_name=table_name,