**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/hooks/bigquery.py
:type labels: dict
        :param encryption_configuration: [Optional] Custom encryption configuration (e.g., Cloud KMS keys).
            **Example**: ::
                encryption_configuration = {
                    "kmsKeyName": "projects/testp/locations/us/keyRings/test-kr/cryptoKeys/test-key"
                }
        :type encryption_configuration: dict
        """
        warnings.warn(
            "This method is deprecated. Please use `BigQueryHook.insert_job` method.", DeprecationWarning
        )
        if not self.project_id:
            raise ValueError("The project_id should be set")
        source_project_dataset_tables = (
            [source_project_dataset_tables]
            if not isinstance(source_project_dataset_tables, list)
            else source_project_dataset_tables
        )
        source_project_dataset_tables_fixup = []
        for source_project_dataset_table in source_project_dataset_tables:
            source_project, source_dataset, source_table = _split_tablename(
                table_input=source_project_dataset_table,
                default_project_id=self.project_id,
                var_name='source_project_dataset_table',
            )
            source_project_dataset_tables_fixup.append(
                {'projectId': source_project, 'datasetId': source_dataset, 'tableId': source_table}
            )
        destination_project, destination_dataset, destination_table = _split_tablename(
            table_input=destination_project_dataset_table, default_project_id=self.project_id