### 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 name: Name of the job (default airflow-spark). (templated)
    :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 (templated)
    :param env_vars: Environment variables for spark-submit. It supports yarn and k8s mode too. (templated)
    :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
    """
    template_fields: Sequence[str] = (
        "_application",
        "_conf",
        "_files",
        "_py_files",
        "_jars",
        "_driver_class_path",
        "_packages",
        "_exclude_packages",
        "_keytab",
        "_principal",
        "_proxy_user",
        "_name",
        "_application_args",
        "_env_vars",
    )
    ui_color = WEB_COLORS["LIGHTORANGE"]
    def __init__(