### Description

We have a use case where we would like to run a job runs in EMR Serverless where the job name should contain the start date.
For example: `name="[{{ ds }}] testing"`.

The solution presented in [31711](https://github.com/apache/airflow/issues/31711) does not work, because command
[self.name = name or self.config.pop("name", f"emr_serverless_job_airflow_{uuid4()}")](https://github.com/apache/airflow/blob/main/airflow/providers/amazon/aws/operators/emr.py#L1229) 
removes the `name` parameter from the `config` when initializing the `EmrServerlessStartJobOperator` operator

### Use case/motivation

_No response_

### Related issues

https://github.com/apache/airflow/issues/31711

### Are you willing to submit a PR?

- [ ] 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)

region_name=self._emr_hook.conn_region_name,
                aws_partition=self._emr_hook.conn_partition,
                job_flow_id=self._job_flow_id,
                log_uri=get_log_uri(emr_client=self._emr_hook.conn, job_flow_id=self._job_flow_id),
            )
        if self.deferrable:
            self.defer(
                trigger=EmrCreateJobFlowTrigger(
                    job_flow_id=self._job_flow_id,
                    aws_conn_id=self.aws_conn_id,
                    poll_interval=self.waiter_delay,
                    max_attempts=self.waiter_max_attempts,
                ),
                method_name="execute_complete",
                
                
                timeout=timedelta(seconds=self.waiter_max_attempts * self.waiter_delay + 60),
            )
        if self.wait_for_completion:
            self._emr_hook.get_waiter("job_flow_waiting").wait(
                ClusterId=self._job_flow_id,
                WaiterConfig=prune_dict(
                    {
                        "Delay": self.waiter_delay,
                        "MaxAttempts": self.waiter_max_attempts,
                    }
                ),
            )
        return self._job_flow_id
    def execute_complete(self, context, event=None):