Languages are pretty irrelevant. I use C# personally just because I like it, but others use Matlab, R, or Java. If someone came on board and could make us money in Smalltalk or QBasic, we'd let them use that. :)
Data can come from numerous places depending on your licensing budget. For an initial analysis you can go to Yahoo! for daily prices; data reliability isn't great but you get what you pay for there. Bloomberg provides great data (assuming you guys have a Bloomberg tutorial), but make sure to read their T&C! They have very strict rules about taking data off machines, etc. Other sources are places like Tickdata.com and similar vendors whose sole purpose is to provide you with clean, reliable data.
As far as frameworks go, to be honest most of the code is created from scratch. My C# framework is around 50,000 lines plus the code for individual models. It still feels like it's only about 5% of what I want it to be. If I were to start over again, I'd probably go with R because so many computational finance people have contributed to it and its graphing/plotting/statistics features are amazing.
Are you in a position to change how your company approaches modeling? We're currently expanding into consulting and services as well. If you want to talk more about that, check my profile and send me an email. We could probably help you guys get started in the area or work with your team to develop custom models.
The book looks like it may be really good. Most of what I've learned about automated execution has been through the long road of trial and error. Most of those topics in the book are important, though it seems based on the ToC that the content may fizzle out just when it gets to the good stuff.