Same experience. I think the most interesting and most public example of such a pipeline is Google/ building a search index. This is also where a lot of the methods originally came from.
Nowadays a lot of this will be used to build recommendation systems / feature pipelines for ML.
These are a bit too advanced examples. Think of simple descriptive statistics which is still so important yet not sexy as ML/DL/AI. ML is great, but the main usage behind these data technologies is still simple business intelligence.
Every business in every market need to understand what is going on with their processes. How many sales did I do yesterday, last week, last month, compared to last year, in which stores, what is the average basket amount, customers buy what with what, what size t-shirt do I sell the most, etc.
