### Apache Airflow Provider(s)

dbt-cloud

### Versions of Apache Airflow Providers

```
apache-airflow-providers-dbt-cloud==2.2.0
```

### Apache Airflow version

2.2.5

### Operating System

Ubuntu 18.04

### Deployment

Composer

### Deployment details

_No response_

### What happened

Instructing `DbtCloudGetJobRunArtifactOperator` to save results in a path like `{{ var.value.base_path }}/dbt_run_warehouse/{{ run_id }}/run_results.json` fails because it contains a path not created yet.


```
Traceback (most recent call last):
  File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/dbt/cloud/operators/dbt.py", line 216, in execute
    with open(self.output_file_name, "w") as file:
FileNotFoundError: [Errno 2] No such file or directory: '/home/airflow/gcs/data/dbt/dbt_run_warehouse/manual__2022-10-17T22:18:25.469526+00:00/run_results.json'
```


### What you think should happen instead

It should create this path and dump the content of the requested artefact

### How to reproduce

```python
with DAG('test') as dag:
  DbtCloudGetJobRunArtifactOperator(
    task_id='dbt_run_warehouse',
    run_id=12341234,
    path='run_results.json',
    output_file_name='{{ var.value.dbt_base_target_folder }}/dbt_run_warehouse/{{ run_id }}/run_results.json'
```

     

### Anything else

_No response_

### 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)

def setup_method(self):
        self.dag = DAG("test_dbt_cloud_job_run_op", start_date=DEFAULT_DATE)
        self.mock_ti = MagicMock()
        self.mock_context = {"ti": self.mock_ti}
        self.config = {
            "job_id": JOB_ID,
            "check_interval": 1,
            "timeout": 3,
            "steps_override": ["dbt run --select my_first_dbt_model"],
            "schema_override": "another_schema",
            "additional_run_config": {"threads_override": 8},
        }
    @patch.object(DbtCloudHook, "trigger_job_run", return_value=MagicMock(**DEFAULT_ACCOUNT_JOB_RUN_RESPONSE))
    @pytest.mark.parametrize(
        "job_run_status, expected_output",
        [
            (DbtCloudJobRunStatus.SUCCESS.value, "success"),
            (DbtCloudJobRunStatus.ERROR.value, "exception"),
            (DbtCloudJobRunStatus.CANCELLED.value, "exception"),
            (DbtCloudJobRunStatus.RUNNING.value, "timeout"),
            (DbtCloudJobRunStatus.QUEUED.value, "timeout"),
            (DbtCloudJobRunStatus.STARTING.value, "timeout"),
        ],
    )
    @pytest.mark.parametrize(
        "conn_id, account_id",
        [(ACCOUNT_ID_CONN, None), (NO_ACCOUNT_ID_CONN, ACCOUNT_ID)],
        ids=["default_account", "explicit_account"],
    )
    def test_execute_wait_for_termination(