### 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)

def test_init_with_named_parameters(self):
        """
        Test the initializer with the named parameters.
        """
        op = DatabricksRunNowOperator(job_id=JOB_ID, task_id=TASK_ID)
        expected = utils.normalise_json_content({"job_id": 42})
        assert expected == op.json
    def test_init_with_json(self):
        """
        Test the initializer with json data.
        """
        json = {
            "notebook_params": NOTEBOOK_PARAMS,
            "jar_params": JAR_PARAMS,
            "python_params": PYTHON_PARAMS,
            "spark_submit_params": SPARK_SUBMIT_PARAMS,
            "job_id": JOB_ID,
        }
        op = DatabricksRunNowOperator(task_id=TASK_ID, json=json)
        expected = utils.normalise_json_content(
            {
                "notebook_params": NOTEBOOK_PARAMS,
                "jar_params": JAR_PARAMS,
                "python_params": PYTHON_PARAMS,
                "spark_submit_params": SPARK_SUBMIT_PARAMS,
                "job_id": JOB_ID,
            }
        )
        assert expected == op.json
    def test_init_with_merging(self):