### Description

Allow an Airflow DAG to define a Databricks job with the `api/2.1/jobs/create` (or `api/2.1/jobs/reset`) endpoint then run that same job with the `api/2.1/jobs/run-now` endpoint. This would give similar capabilities as the DatabricksSubmitRun operator, but the `api/2.1/jobs/create` endpoint supports additional parameters that the `api/2.1/jobs/runs/submit` doesn't (e.g. `job_clusters`, `email_notifications`, etc.).

### Use case/motivation

Create and run a Databricks job all in the Airflow DAG. Currently, DatabricksSubmitRun operator uses the `api/2.1/jobs/runs/submit` endpoint which doesn't support all features and creates runs that aren't tied to a job in the Databricks UI. Also, DatabricksRunNow operator requires you to define the job either directly in the Databricks UI or through a separate CI/CD pipeline causing the headache of having to change code in multiple places.

### Related issues

_No response_

### Are you willing to submit a PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""
        Cancel the run.
        :param run_id: id of the run
        """
        json = {"run_id": run_id}
        self._do_api_call(CANCEL_RUN_ENDPOINT, json)
    def cancel_all_runs(self, job_id: int) -> None:
        """
        Cancel all active runs of a job asynchronously.
        :param job_id: The canonical identifier of the job to cancel all runs of
        """
        json = {"job_id": job_id}
        self._do_api_call(CANCEL_ALL_RUNS_ENDPOINT, json)
    def delete_run(self, run_id: int) -> None:
        """
        Delete a non-active run.
        :param run_id: id of the run
        """
        json = {"run_id": run_id}
        self._do_api_call(DELETE_RUN_ENDPOINT, json)
    def repair_run(self, json: dict) -> None:
        """
        Re-run one or more tasks.
        :param json: repair a job run.
        """
        self._do_api_call(REPAIR_RUN_ENDPOINT, json)
    def get_cluster_state(self, cluster_id: str) -> ClusterState: