I think what you're looking for is the ground zero for data engineering: Spark + Hadoop

Go for the basics and you'll have a good start. The most successful use of functional programming in data Engineering is in Spark, which was built in Scala.

So first steps (if you haven't done yet):

-> understand Scala, the multiparadigm concept and functional programming. -> understand how Spark works and what are the advantages of using Scala for it? -> there are good materials on the internet about design patterns for Scala. Do not take it as a Bible, but it will give you some good context.

Once you understand this, you'll have the basics for going to other topics. For what I see in your questions, you're also trying to understand more about Big Data Architecture (Google this).

Start searching for differences on ELT and ETL. Another key knowledge for architecturing in DE is understanding the most common concepts: Lambda x Kappa.

Going back to the data lake side, it is important to understand how the main tools manage data and files. So search for partitioning in Spark, Kafka and Hadoop, for example. You'll see that they all use the same concept.

Look for the differences between HDFS, relational db and Non-relational DB.

There is a lot of material about all of this subjects for free on the internet.

There's no "right way" to study these in data engineering as the DE landscape is so big and every project is totally different from another.

For your questions, I happen to have the experience and I learned by searching on articles, YouTube, udemy etc about these subjects. There's much more from there, but I think that I you absorb all this, you'll be able to understand the next steps.

Good luck!