Job created from library doesn't respect project default `default_query_job_timeout_ms` config

### Expected behaviour
BQ jobs created/initated via this library should respect the `default_query_job_timeout_ms` set on the BQ project.

### Issue
Hey team, just raising an inquiry about the second half of my comment raised here https://github.com/dbt-labs/dbt-bigquery/issues/231. From what I can tell, a query created from this library does not respect the `default_query_job_timeout_ms` set on the BQ project for some reason.

#### Environment details

- OS type and version: macOS / Ventura 13.4.1
- Python version: `Python 3.9.13`
- pip version: `pip 23.2.1`
- `google-cloud-bigquery` version:

```
name: google-cloud-bigquery
Version: 3.11.4
Summary: Google BigQuery API client library
Home-page: https://github.com/googleapis/python-bigquery
Author: Google LLC
Author-email: googleapis-packages@google.com
License: Apache 2.0
Location: /Users/jeremy/src/dbt-basic/venv_dbt_1.5.latest/lib/python3.9/site-packages
Requires: google-api-core, google-cloud-core, google-resumable-media, grpcio, packaging, proto-plus, protobuf, python-dateutil, requests
Required-by: dbt-bigquery
```

#### Steps to reproduce

1. Set the `default_query_job_timeout_ms` to be 5 minutes:

```sql
alter project `cse-sandbox-319708` set options (`region-us.default_query_job_timeout_ms` = 300000);
```

2. Run a query/job from the BQ UI that takes > 5 minutes:


Notice that we run into an error at 5 minutes - as expected.

3. Run a query/job from python using this library that takes > 5 minutes (see Python code example below):


Notice that on the BQ side - the query/job completes taking > 5 minutes (6 m 41 s) - this is unexpected.

#### Code example

```python
from google.cloud import bigquery

client = bigquery.Client()

# Perform a query.
query = """
call dbt_jyeo.fake_sleep(400);
select * from `region-us.INFORMATION_SCHEMA.PROJECT_OPTIONS`;
"""

query_job = client.query(query) # API request
rows = query_job.result() # Waits for query to finish

for row in rows:
print(row)
```

#### Stack trace
There are no errors per se so nothing to call out here.