### Apache Airflow version

Other Airflow 2 version (please specify below)

### What happened

Airflow version: 2.5.3
Description: While using BigQueryCreateExternalTableOperator, when we to create external table on top of parquet files located in GCS, airflow shows below error:
google.api_core.exceptions.BadRequest: 400 POST ... failed. CsvOptions can only be specified if storage format is CSV.

No csvOptions are mentioned while passing the source_format as Parquet. There seems to be an issue with bigquery.py hook.

### What you think should happen instead

_No response_

### How to reproduce

While using BigQueryCreateExternalTableOperator, try to create external table on top of parquet files located in GCS. Sample usage:
`create_external_table = BigQueryCreateExternalTableOperator(
    task_id="create_external_table",
    destination_project_dataset_table="table_name",
    bucket=GCS_BUCKET_NAME,
    source_objects=[<list of URIs of parquet files>],
    source_format="PARQUET",
    autodetect=True,
    gcp_conn_id="gcp_conn_id",
    google_cloud_storage_conn_id="test_conn_id",
)`

### Operating System

-

### Versions of Apache Airflow Providers

_No response_

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit 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)

self.job_id = [
                self.hook.run_query(
                    sql=s,
                    destination_dataset_table=self.destination_dataset_table,
                    write_disposition=self.write_disposition,
                    allow_large_results=self.allow_large_results,
                    flatten_results=self.flatten_results,
                    udf_config=self.udf_config,
                    maximum_billing_tier=self.maximum_billing_tier,
                    maximum_bytes_billed=self.maximum_bytes_billed,
                    create_disposition=self.create_disposition,
                    query_params=self.query_params,
                    labels=self.labels,
                    schema_update_options=self.schema_update_options,
                    priority=self.priority,
                    time_partitioning=self.time_partitioning,
                    api_resource_configs=self.api_resource_configs,
                    cluster_fields=self.cluster_fields,
                    encryption_configuration=self.encryption_configuration,
                )
                for s in self.sql
            ]
        else:
            raise AirflowException(f"argument 'sql' of type {type(str)} is neither a string nor an iterable")
        project_id = self.hook.project_id
        if project_id:
            job_id_path = convert_job_id(job_id=self.job_id, project_id=project_id, location=self.location)
            context["task_instance"].xcom_push(key="job_id_path", value=job_id_path)
        return self.job_id
    def on_kill(self) -> None: