### 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, partial_func: Callable, result_key: str, max_results: int | None = None
    ) -> list[dict]:
        """
        All AWS boto3 list_* requests return results in batches (if the key "NextToken" is contained in the
        result, there are more results to fetch). The default AWS batch size is 10, and configurable up to
        100. This function iteratively loads all results (or up to a given maximum).
        Each boto3 list_* function returns the results in a list with a different name. The key of this
        structure must be given to iterate over the results, e.g. "TransformJobSummaries" for
        list_transform_jobs().
        :param partial_func: boto3 function with arguments
        :param result_key: the result key to iterate over
        :param max_results: maximum number of results to return (None = infinite)
        :return: Results of the list_* request
        """
        sagemaker_max_results = 100  
        results: list[dict] = []
        next_token = None
        while True:
            kwargs = {}
            if next_token is not None:
                kwargs["NextToken"] = next_token
            if max_results is None: