Apache Airflow version: 1.10.*
BackPort Packages version: 2020.10.29rc1

What happened:

BigQueryInsertJobOperator tries to start a BigQuery job by specifying a job_id which is a combination of dag_id, task_id, execution_date and an additional uniqueness_suffix.

https://github.com/PolideaInternal/airflow/blob/e5307990adb49a5a1c1c88a029940682efee0f9e/airflow/providers/google/cloud/operators/bigquery.py#L2073

However, it would appear that the regex pattern that is attempting to remove the `+` character is not correct as this still remain in `job_id` after `re.sub` is applied.

https://github.com/PolideaInternal/airflow/blob/e5307990adb49a5a1c1c88a029940682efee0f9e/airflow/providers/google/cloud/operators/bigquery.py#L2073

`Invalid job ID "airflow_my_test_dag_v1_test_2020_10_01T00_00_00+00_00_27f69de5cd17a012f3c89d414a70fe64". Job IDs must be alphanumeric (plus underscores and dashes) and must be at most 1024 characters long.
`  

How to reproduce it:

- Create a DAG with the name my-test-dag-v1.
- Run any query against BigQuery using this operator
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