Executor = worker in databricks workflow context.
So indeed, if you set executor.cores = 4 and have 16 cores you would not use 12 cores.
So adjusting spark.executor.cores and spark.task.cpus might be a good idea.
There is also the option to define this dynamically (on job level!) with spark.dynamicAllocation.enabled.