I'm really excited about the state of data infrastructure and the emergence of the data lake. I feel like the technical aspects of data engineering is reduced to getting data into some cloud storage (s3) as parquet. Transforms are "solved" using ELT from the data lake, or streaming using kafka/spark.
I think executing this in orgs with legacy data technologies is hard but it is much more a people problem than a tech problem. In orgs that have achieved this foundation it's really cool to see the business and analytic impact to the company.
Snowflake (and others) will let you either pull that in and query it or as an external query that queries it in place. You can, if it makes sense for your use case, now just T from the data lake.
I think executing this in orgs with legacy data technologies is hard but it is much more a people problem than a tech problem. In orgs that have achieved this foundation it's really cool to see the business and analytic impact to the company.