So in a similar vein as, data engineers being people who USE things like Redshift/Snowflake/Spark/etc., but are distinct from the category of people who actually build those underlying frameworks or databases?
In some sense, the expansion of the role of data engineering as a discipline unto itself is largely enabled by the commoditization of cloud data warehouses and open source tooling supporting the function of data engineering. Likewise, the more foundational AI that gets created and eventually commoditized, the more an additional layer of "AI engineers" can build on top of those tools and apply them to real world business problems (many of which are unsexy... I wonder what the "AI engineer" equivalent unit of work will be, compared to the standard "load these CSVa into a data warehouse" base unit task of data engineers).
In some sense, the expansion of the role of data engineering as a discipline unto itself is largely enabled by the commoditization of cloud data warehouses and open source tooling supporting the function of data engineering. Likewise, the more foundational AI that gets created and eventually commoditized, the more an additional layer of "AI engineers" can build on top of those tools and apply them to real world business problems (many of which are unsexy... I wonder what the "AI engineer" equivalent unit of work will be, compared to the standard "load these CSVa into a data warehouse" base unit task of data engineers).