Yes, it is an appropriate option to use DESeq2 in your case. Just note that DESeq2 will take into account all the genes to (1) estimate dispersion and (2) normalize your libraries using the median of ratios method. So even if in the end you only look at two genes, all genes are used in the analysis, which is good because it make it more robust/powerful.
There are quite a few DESeq2 examples/pipelines out there. For instance, this one is well explained and complete.