[bigger_cheese]

I think my job is similar to yours. My background is in engineering at an industrial manufacturing plant.

I have some of the same issues. The Engineers here tend to reach for spreadsheets first (or Access databases - these things are everywhere at my work) and inevitably they run into scaling problems and end up with a huge bloated mess. I step in to re-architecture these monstrosities (using "real" databases when necessary).

The other big part of my day to day work is modelling and data analysis. Usually regression based stuff and LP optimization problems (SAS is very good for this) especially around yield and quality control. The venerable excel "solver" plugin is often abused very heavily by engineers and is not always the ideal solution.

The person who I took over from was a Stats guy and the original job title was "Process Statistician" my boss has since retitled my role "Data Management Engineer". I still think of myself as an engineer first and foremost and a "data" person second.

I use SAS heavily. We have kind of gone in the opposite direction to you. I have rewritten some of our models in the past from C++ into SAS mostly for ease of maintenance because SAS is better understood by the non programmers (Most of the Engineers here do not have a programming/CS background and those that do tend to either know Fortran or Visual Basic very few grasp C/C++ very well). Speed is not really any issue but opaqueness and ease of maintanece is.

I'd like to learn R because I have heard it is very similar to SAS but more transferable to outside companies. Julia is the other language I've got my eye on I have heard it is somewhat similar to MATLAB which is used for some modelling work here.