**Apache Airflow version**: 2.0.2


**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): NA

**Environment**: MWAA and Locally

- **Cloud provider or hardware configuration**: AWS
- **OS** (e.g. from /etc/os-release): NA
- **Kernel** (e.g. `uname -a`): NA
- **Install tools**: NA
- **Others**: NA

**What happened**:

When calling the SagemakerProcessingOperator sometimes get: "botocore.exceptions.ClientError: An error occurred (ThrottlingException)" due to excessive ListProcessingJobs operations.

**What you expected to happen**:

The job should have started without timing out. I believe one fix would be to use the `NameContains` functionality of boto3 [list_processing_jobs](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.list_processing_jobs) so you don't have to paginate as is occurring [here](https://github.com/apache/airflow/blob/main/airflow/providers/amazon/aws/hooks/sagemaker.py#L916). 

**How to reproduce it**:

If you incrementally create Sagemaker Processing jobs you will eventually see the Throttling as the pagination increases.

**Anything else we need to know**:

This looks like it is happening when the account already has a lot of former Sagemaker Processing jobs.
airflow/providers/amazon/aws/hooks/sagemaker.py
self,
        job_name: str,
        non_terminal_states: set,
        failed_states: set,
        wait_for_completion: bool,
        check_interval: int,
        max_ingestion_time: Optional[int] = None,
    ):
        """
        Display the logs for a given training job, optionally tailing them until the
        job is complete.
        :param job_name: name of the training job to check status and display logs for
        :type job_name: str
        :param non_terminal_states: the set of non_terminal states
        :type non_terminal_states: set
        :param failed_states: the set of failed states
        :type failed_states: set
        :param wait_for_completion: Whether to keep looking for new log entries
            until the job completes
        :type wait_for_completion: bool
        :param check_interval: The interval in seconds between polling for new log entries and job completion
        :type check_interval: int
        :param max_ingestion_time: the maximum ingestion time in seconds. Any
            SageMaker jobs that run longer than this will fail. Setting this to
            None implies no timeout for any SageMaker job.
        :type max_ingestion_time: int