A Spark engineer must select an appropriate deployment mode for the Spark jobs.

In Apache Spark's cluster mode:

"The driver program runs on the cluster’s worker node instead of the client’s local machine. This allows the driver to be close to the data and other executors, reducing network overhead and improving fault tolerance for production jobs."

(Source: Apache Spark documentation – Cluster Mode Overview)

This deployment is ideal for production environments where the job is submitted from a gateway node, and Spark manages the driver lifecycle on the cluster itself.

Option A is partially true but less specific than D.

Option B is incorrect: the driver never executes all tasks; executors handle distributed tasks.

Option C describes client mode, not cluster mode.