I checked a few days ago and the revenue per employee at big tech is eerily similar to "Biglaw" and non retail banking (Jones day, >200k entry level, goldman is similar) at 1-2mil per employee. One could argue the market for IB/trading has been saturated by applicants for years but they pay is still well above norms ~>150k entry level. Pretty interesting.
Does this logic work for lawyers? "Biglaw" firms are similar to FAANG in that it is a handful of companies that offer very high comp (235k for first year). There is a deluge of folks that apply from all universities to biglaw but generally they primarily hire from top tier law schools and even then not all make it.
Similar for Big 3 consulting firms (BCG, Bain, McKinsey) in that there is a huge application pool for positions but they are difficult to get and provide high pay.
Interestingly revenue per employee (1.2 - 1.8 mil per employee) at biglaw companies is similar to FAANG although i'd guess biglaw margins are higher as you have less other costs (infra).
Twitter has ads serving infra, recommendation systems (timeline, notifications, events, users), user generated events, prediction systems (ads), user graphs. The complexity is from processing and persisting exabytes of data in company owned datacenters. eg. Twitter stores images, videos, user events, user data, tweets/replies. WhatsApp has little persistence outside of metadata maybe? But your messages are not stored in a FB datacenter and if they are I'd be concerned. You can read about their infra in their blog. Comparing p2p messaging versus a distributed social media site with mountains of data and years of iteration in ML systems does not make sense.
