I've also done the 40 GB/day of NYSE TAQ data financial analysis thing, and the 1000+ trades/second real-time financial analytics thing. And I work on Google Search, and have a passing familiarity with how other Google products scale.
The scaling challenges of batch financial models vs. real-time financial processing vs. information retrieval vs. email vs. social products are very different. Even going from a model of the web where it's static and changes every few months (like Google of 2004) to one where sites get update every few minutes and users expect to see the updates immediately in search results (like Google of today) requires vastly different technology.
The main thing about scaling that I've learned from working at a couple places that require it is to go into it with a fresh mind each time, and really pay attention to what the requirements are and what you can cut corners on. There're some general principles you should know (eg. Jeff Dean's "Numbers you should know", memory is much faster than disk, cut out layers of abstraction that you don't need), but in order to apply them effectively, you really need to pay attention to the details of your problem domain.
If you think you can solve Twitter's scaling problems, they're hiring, they're pre-IPO, and they're probably giving out decent chunks of stock.
