### 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)

run_state = RunState("TERMINATED", "SUCCESS", "")
        assert run_state.is_successful
    def test_to_json(self):
        run_state = RunState("TERMINATED", "SUCCESS", "")
        expected = json.dumps(
            {"life_cycle_state": "TERMINATED", "result_state": "SUCCESS", "state_message": ""}
        )
        assert expected == run_state.to_json()
    def test_from_json(self):
        state = {"life_cycle_state": "TERMINATED", "result_state": "SUCCESS", "state_message": ""}
        expected = RunState("TERMINATED", "SUCCESS", "")
        assert expected == RunState.from_json(json.dumps(state))
class TestClusterState:
    def test_is_terminal_true(self):
        terminal_states = ["TERMINATING", "TERMINATED", "ERROR", "UNKNOWN"]
        for state in terminal_states:
            cluster_state = ClusterState(state, "")
            assert cluster_state.is_terminal
    def test_is_terminal_false(self):
        non_terminal_states = ["PENDING", "RUNNING", "RESTARTING", "RESIZING"]
        for state in non_terminal_states:
            cluster_state = ClusterState(state, "")
            assert not cluster_state.is_terminal
    def test_is_terminal_with_nonexistent_life_cycle_state(self):
        with pytest.raises(AirflowException):
            cluster_state = ClusterState("blah", "")
            assert cluster_state.is_terminal
    def test_is_running(self):