### Apache Airflow Provider(s)

amazon

### Versions of Apache Airflow Providers



apache-airflow-providers-amazon | 2.4.0

### Apache Airflow version

2.2.3 (latest released)

### Operating System

Amazon Linux 2

### Deployment

MWAA

### Deployment details

_No response_

### What happened

Sagemaker Processing Operator no longer honors the `action_if_job_exists` param and always fails creation of a new processing job is a job with the name already exists. 

This happens because in a recent change, the function responsible for executing the job no longer honors the increment setting:

Change that breaks the increment: https://github.com/apache/airflow/commit/96dd70348ad7e31cfeae6d21af70671b41551fe9

New code: https://github.com/apache/airflow/blob/6734eb1d09a99dc519e89a59e2086cef09a87098/airflow/providers/amazon/aws/operators/sagemaker.py#L167

  

### What you expected to happen

When Sagemaker Processing operator is called with a job-name that already exists, the job creation should succeed with a name that is incremented by 1.   

### How to reproduce

invoke SageMakerProcessingOperator twice with the same job name while keeping action_if_job_exists as 'increment'.   

### Anything else

_No response_

### Are you willing to submit 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, name_contains: str | None = None, max_results: int | None = None, **kwargs
    ) -> list[dict]:
        """
        This method wraps boto3's `list_training_jobs`. The training job name and max results are configurable
        via arguments. Other arguments are not, and should be provided via kwargs. Note boto3 expects these in
        CamelCase format, for example:
        .. code-block:: python
            list_training_jobs(name_contains="myjob", StatusEquals="Failed")
        .. seealso::
            https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.list_training_jobs
        :param name_contains: (optional) partial name to match
        :param max_results: (optional) maximum number of results to return. None returns infinite results
        :param kwargs: (optional) kwargs to boto3's list_training_jobs method
        :return: results of the list_training_jobs request
        """
        config, max_results = self._preprocess_list_request_args(name_contains, max_results, **kwargs)
        list_training_jobs_request = partial(self.get_conn().list_training_jobs, **config)
        results = self._list_request(
            list_training_jobs_request, "TrainingJobSummaries", max_results=max_results
        )
        return results
    def list_transform_jobs(