I see many books on Python listed. It's a good language for data analysis and scientific computing, especially with scipy, but there are alternatives, of course. I like Fortran 95, which is available in gcc as gfortran. A relevant book for data scientists would be "Developing Statistical Software in Fortran 95" (2005).
Arrays in Fortran 90+ are a powerful feature -- there are whole array operations and operations on array slices, as in Matlab and Python with numpy. It's easy to allocate multidimensional arrays. Compilers are good at optimizing code -- if it's easiest to do something with loops you can go ahead and not worry about vectorizing the code, as you might with R or Matlab. There is a lot of statistics code in Fortran, so it's good to have at least a reading knowledge of it.
This is why I'm so in love with pandas (pandas.pydata.org) -- Wes McKinney did the world a favor creating a library with powerful, manipulable multidimensional data structures
