**Description**

`BigQueryInsertJobOperator` requires the submission of a `configuration` parameter in the form of a dict.  Unfortunately, if this contains a large SQL query - especially one that is formatted with new lines - then this cannot currently be rendered very nicely in the UI.

<img width="1670" alt="Screenshot 2021-07-15 at 15 39 33" src="https://user-images.githubusercontent.com/967119/125806943-839d57a9-d4a0-492d-b130-06432b095239.png">

**Use case / motivation**

The issue with this is that it's impossible to copy and paste the rendered query out of the Airflow UI, into a BigQuery browser and run it without lots of manual edits which is time wasted when troubleshooting problems.

**Are you willing to submit a PR?**

Yes.  My current thought process around this would be to add an optional SQL parameter to the operator which, if provided, would be added into the configuration and could therefore have its own template field and SQL renderer.

e.g.

<img width="1570" alt="Screenshot 2021-07-14 at 14 18 09" src="https://user-images.githubusercontent.com/967119/125808200-5f30b8f4-4def-48a7-8223-82afdc65c973.png">


airflow/providers/google/cloud/operators/bigquery.py
"""
    Performs checks against BigQuery. The ``BigQueryCheckOperator`` expects
    a sql query that will return a single row. Each value on that
    first row is evaluated using python ``bool`` casting. If any of the
    values return ``False`` the check is failed and errors out.
    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:BigQueryCheckOperator`
    Note that Python bool casting evals the following as ``False``:
    * ``False``
    * ``0``
    * Empty string (``""``)
    * Empty list (``[]``)
    * Empty dictionary or set (``{}``)
    Given a query like ``SELECT COUNT(*) FROM foo``, it will fail only if
    the count ``== 0``. You can craft much more complex query that could,
    for instance, check that the table has the same number of rows as
    the source table upstream, or that the count of today's partition is
    greater than yesterday's partition, or that a set of metrics are less
    than 3 standard deviation for the 7 day average.
    This operator can be used as a data quality check in your pipeline, and
    depending on where you put it in your DAG, you have the choice to
    stop the critical path, preventing from
    publishing dubious data, or on the side and receive email alerts
    without stopping the progress of the DAG.
    :param sql: the sql to be executed
    :type sql: str
    :param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud.
    :type gcp_conn_id: str