In an Apache Spark based data engineering/analytics project - what would a design document template look like ?

Of course answer depends on the business/project requirements.

But will the design document "template" contain the following aspects ?

Am I missing something ?

My current list of aspects in the design template -

(1) Tables/Views to be created (if any) in the source system in order to facilitate my project's pipeline(s). For some of the pipelines Kafka topic is the source. (2) Pipeline - schema of the data, estimated data volume per call, format (csv etc.), Kafka topic, frequency of pulling data (daily, weekly etc) from source system, is the data pulled as needed or per a schedule or based on an event, connectivity etc. (3) What kind of data objects will be created to persist the data in the data-lake ? (4) High level statement of all code changes, config changes, and data changes (including movement). (5) Which design standards/best practices are being followed ? Critical design decisions to optimize/improve pipeline performance. (6) Which regulatory compliance standards are being applied and how ? (7) Which aggregation objects/views are to be created so that data and analytics reports can be served.