### 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)

]
        )
        if not table_resource:
            warnings.warn(
                "Passing table parameters via keywords arguments will be deprecated. "
                "Please provide table definition using `table_resource` parameter.",
                AirflowProviderDeprecationWarning,
                stacklevel=2,
            )
            if not bucket:
                raise ValueError("`bucket` is required when not using `table_resource`.")
            if not gcs_schema_bucket:
                gcs_schema_bucket = bucket
            if not source_objects:
                raise ValueError("`source_objects` is required when not using `table_resource`.")
            if not source_format:
                source_format = "CSV"
            if not compression:
                compression = "NONE"
            if not skip_leading_rows:
                skip_leading_rows = 0
            if not field_delimiter:
                field_delimiter = ","
            if not destination_project_dataset_table:
                raise ValueError(
                    "`destination_project_dataset_table` is required when not using `table_resource`."
                )
            self.bucket = bucket
            self.source_objects = source_objects
            self.schema_object = schema_object