no, it should not. The point of modern data warehouses like Snowflake is that you run the transformations in the warehouse, vs. some external transformation layer (think Informatica).

In the old approach, you would run the transform BEFORE loading data into the warehouse. The disadvantage of that approach is that you loose all fidelity of the raw data.

In the new approach (Airbyte's approach), you load the raw data into the warehouse, and then run your transform jobs in the warehouse. You can do that because modern warehouses are cheap and scalable. The benefit of that approach is that you keep your raw data with all its fidelity, opening up endless opportunities for exploratory slicing and dicing.

That's why it's called "ELT" (new) these days, to distinguish from "ELT" (old).

If you are interested, John (one of the co-founders) wrote an article about how we are imagining ELT evolving. https://airbyte.io/articles/data-engineering-thoughts/why-th...

ETL and ELT are similar but separate things. ELT has been popular for a few years now, and the data lake approach as well as cheap storage has solidified it as the current preferred way to do a data warehouse.