### Description


spark-submit command has one of the options to pass the properties file as argument. Instead of loading multiple key, value via --conf option, this will help to load extra properties from the file path. While we have support for most of the arguments supported in spark-submit command in SparkSubmitOperator, this one `property-files` is missing. Could that be included?
```[root@airflow ~]# spark-submit --help
Usage: spark-submit [options] <app jar | python file | R file> [app arguments]
Usage: spark-submit --kill [submission ID] --master [spark://...]
Usage: spark-submit --status [submission ID] --master [spark://...]
Usage: spark-submit run-example [options] example-class [example args]

Options:

 --conf, -c PROP=VALUE       Arbitrary Spark configuration property.
  --properties-file FILE      Path to a file from which to load extra properties. If not
                              specified, this will look for conf/spark-defaults.conf.
```


### Use case/motivation

Add the property-files as one of the options to pass in the SparkSubmitOperator to load the extra config properties as file

### Related issues

_No response_

### Are you willing to submit a 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)

:param repositories: Comma-separated list of additional remote repositories to search
        for the maven coordinates given with 'packages'
    :param total_executor_cores: (Standalone & Mesos only) Total cores for all executors
        (Default: all the available cores on the worker)
    :param executor_cores: (Standalone, YARN and Kubernetes only) Number of cores per
        executor (Default: 2)
    :param executor_memory: Memory per executor (e.g. 1000M, 2G) (Default: 1G)
    :param driver_memory: Memory allocated to the driver (e.g. 1000M, 2G) (Default: 1G)
    :param keytab: Full path to the file that contains the keytab
    :param principal: The name of the kerberos principal used for keytab
    :param proxy_user: User to impersonate when submitting the application
    :param name: Name of the job (default airflow-spark)
    :param num_executors: Number of executors to launch
    :param status_poll_interval: Seconds to wait between polls of driver status in cluster
        mode (Default: 1)
    :param application_args: Arguments for the application being submitted
    :param env_vars: Environment variables for spark-submit. It
        supports yarn and k8s mode too.
    :param verbose: Whether to pass the verbose flag to spark-submit process for debugging
    :param spark_binary: The command to use for spark submit.
                         Some distros may use spark2-submit or spark3-submit.
    :param use_krb5ccache: if True, configure spark to use ticket cache instead of relying
        on keytab for Kerberos login
    """
    conn_name_attr = "conn_id"
    default_conn_name = "spark_default"
    conn_type = "spark"
    hook_name = "Spark"
    @classmethod
    def get_ui_field_behaviour(cls) -> dict[str, Any]: