Oh I don't know about that. Programming languages are force multipliers, and each language has a different force coefficients for different problem domains. They are not all equivalent. They have their different points of leverage, and simply being good in one does not mean you can solve problems in any domain with ease. In fact the wrong programming language can often be harmful if it's ill-suited to the problem at hand, and especially if it contorts your mental model of what you can do with the data.

One example I encounter a lot in industry is Excel VBA. I'm fairly good at VBA and have seen very sophisticated code in VBA. I've also seen many basic operations implemented badly in VBA that should not have been written in VBA at all. By solving the problem in VBA, the solution is often "hemmed in" by the constraints of VBA.

For instance, unpivoting data is often done badly in VBA (with for-loops), but is trivial to do well in dplyr or pandas.

So I would say one has to choose one's programming language somewhat carefully. Not any language will do.