### Apache Airflow version

2.5.1

### What happened

We were using GlueJobOperator with Airflow 2.3.3 (official docker image) and it was working well, we didn't specify script file location, because it was inferred from the job name. After migration to 2.5.1 (official docker image) the operator fails if `s3_bucket` and `script_location` are not specified. That's the error I see:
```
Traceback (most recent call last):
  File "/home/airflow/.local/lib/python3.10/site-packages/airflow/providers/amazon/aws/operators/glue.py", line 146, in execute
    glue_job_run = glue_job.initialize_job(self.script_args, self.run_job_kwargs)
  File "/home/airflow/.local/lib/python3.10/site-packages/airflow/providers/amazon/aws/hooks/glue.py", line 155, in initialize_job
    job_name = self.create_or_update_glue_job()
  File "/home/airflow/.local/lib/python3.10/site-packages/airflow/providers/amazon/aws/hooks/glue.py", line 300, in create_or_update_glue_job
    config = self.create_glue_job_config()
  File "/home/airflow/.local/lib/python3.10/site-packages/airflow/providers/amazon/aws/hooks/glue.py", line 97, in create_glue_job_config
    raise ValueError("Could not initialize glue job, error: Specify Parameter `s3_bucket`")
ValueError: Could not initialize glue job, error: Specify Parameter `s3_bucket`
```

### What you think should happen instead

I was expecting that after migration the operator would work the same way.

### How to reproduce

Create a dag with `GlueJobOperator` operator and do not use s3_bucket or script_location arguments

### Operating System

Linux

### Versions of Apache Airflow Providers

apache-airflow-providers-amazon==7.1.0

### Deployment

Docker-Compose

### Deployment details

`apache/airflow:2.5.1-python3.10` Docker image and official docker compose


### Anything else

I believe it was commit #27893 by @romibuzi that introduced this behaviour.

### 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)

iam_role_name: str | None = None,
        create_job_kwargs: dict | None = None,
        *args,
        **kwargs,
    ):
        self.job_name = job_name
        self.desc = desc
        self.concurrent_run_limit = concurrent_run_limit
        self.script_location = script_location
        self.retry_limit = retry_limit
        self.s3_bucket = s3_bucket
        self.role_name = iam_role_name
        self.s3_glue_logs = "logs/glue-logs/"
        self.create_job_kwargs = create_job_kwargs or {}
        worker_type_exists = "WorkerType" in self.create_job_kwargs
        num_workers_exists = "NumberOfWorkers" in self.create_job_kwargs
        if worker_type_exists and num_workers_exists:
            if num_of_dpus is not None:
                raise ValueError("Cannot specify num_of_dpus with custom WorkerType")
        elif not worker_type_exists and num_workers_exists:
            raise ValueError("Need to specify custom WorkerType when specifying NumberOfWorkers")
        elif worker_type_exists and not num_workers_exists:
            raise ValueError("Need to specify NumberOfWorkers when specifying custom WorkerType")
        elif num_of_dpus is None:
            self.num_of_dpus: int | float = 10
        else:
            self.num_of_dpus = num_of_dpus
        kwargs["client_type"] = "glue"
        super().__init__(*args, **kwargs)
    def create_glue_job_config(self) -> dict: