### 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)

self,
        *,
        dynamodb_table_name: str,
        s3_bucket_name: str,
        file_size: int,
        dynamodb_scan_kwargs: dict[str, Any] | None = None,
        s3_key_prefix: str = "",
        process_func: Callable[[dict[str, Any]], bytes] = _convert_item_to_json_bytes,
        **kwargs,
    ) -> None:
        super().__init__(**kwargs)
        self.file_size = file_size
        self.process_func = process_func
        self.dynamodb_table_name = dynamodb_table_name
        self.dynamodb_scan_kwargs = dynamodb_scan_kwargs
        self.s3_bucket_name = s3_bucket_name
        self.s3_key_prefix = s3_key_prefix
    def execute(self, context: Context) -> None: