That example threw me off too because both the numbers and the perspective are non-nonsensical. 90% of the energy draw of those data-centers goes into things like inner video encoding loops, SSD/memcache storage and retrieval, ML algorithms etc.

But the vast majority of those 27.000 engineers do not work on such low level routines, but on things like millions of lines of crufty Python that power Adsense analytics, which are essential for maintaining a revenue stream. Yes, development speed is very important but it's mostly orthogonal to other operational costs if the right tools and architectures are employed.