**Apache Airflow version**: 1.10.*
**BackPort Packages version**: 2020.10.5rc1

**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/apache/airflow/blob/master/airflow/providers/google/cloud/operators/bigquery.py#L2072

However, because BigQuery only accepts alphanumeric (in additon to dashes and underscore) characters then, if a DagID contains a version number whcih includes a `.` character then this will cause the task to fail.

https://cloud.google.com/bigquery/docs/running-jobs#generate-jobid

**How to reproduce it**:
Create a DAG with the name `my-dag-v1.0`.
airflow/providers/google/cloud/operators/bigquery.py
return BigQueryHook(
            gcp_conn_id=self.gcp_conn_id,
            use_legacy_sql=self.use_legacy_sql,
            location=self.location,
            impersonation_chain=self.impersonation_chain,
        )
class BigQueryIntervalCheckOperator(IntervalCheckOperator):
    """
    Checks that the values of metrics given as SQL expressions are within
    a certain tolerance of the ones from days_back before.
    This method constructs a query like so ::
        SELECT {metrics_threshold_dict_key} FROM {table}
        WHERE {date_filter_column}=<date>
    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:BigQueryIntervalCheckOperator`
    :param table: the table name
    :type table: str
    :param days_back: number of days between ds and the ds we want to check
        against. Defaults to 7 days
    :type days_back: int
    :param metrics_threshold: a dictionary of ratios indexed by metrics, for
        example 'COUNT(*)': 1.5 would require a 50 percent or less difference
        between the current day, and the prior days_back.
    :type metrics_threshold: dict
    :param use_legacy_sql: Whether to use legacy SQL (true)