Unix has been 64-bit at lot longer than Windows, and the servers have superior floating point performance over Intel processors.
It is generally easier to secure a Unix box than a Windows box. Mainframes are the best at this, still.
Unix can run on more than 8 processors very effectively: 32, 64, 128.
Unix has superior IO performance tuning/ability over Windows, and SAS is highly IO intensive -- writing and reading the work datasets.
Scripting (batch wrappers) are easier and significantly more powerful than on Windows, generally. Unix shell scripting in bash (Linux), Korne shell, Bourne shell, C Shell, Perl is basic common stock and trade for most any Unix user. Batch scripting on Windows (DOS artifact) has become obscure, and the other Windows command language (VBA) is not as pervasive amongst Windows users on a percentage basis.
Unix boxes are real servers, not that Windows can't be, but the point here, is that EG and PC SAS run on your local box. Regular production runs of SAS jobs should not be dependent on the availability of anyone's particular PC. These jobs are usually scheduled with scheduling products like Control-M. Control-M can run a COBOL job on a mainframe, creating a VSAM file; and then, based on the job's return code as an in-condition, kick of a SAS job on a Unix box that uses SAS/CONNECT and SAS/ACCESS to read the VSAM file directly and do additional stuff with the data, ending in loading an Oracle database sitting on another server. Then the scheduler could kick off another process that runs on a Windows server because some developer wrote a tool that runs only on Windows, and accesses data in some database (Oracle in this case), and the company has to have that tool for some business reason. Through the use of in-conditions and out-conditions, the scheduler can run a process flow without worrying about the timing of when a job might/should complete so that the next one in a series can start. This is superior to using cron on Unix and Scheduled Tasks on Windows to manage processing flows.
EG is a great front end tool for ad hoc analysis and reporting of data. But for regularly performed stuff, you can't beat SAS batch run from a scheduler on a reliable server.