If these are all the employees of that company, then without something like a hypothesis test you can of course descriptively say that males earn more than females in this company. (If it's a representative sample, you would still need to account for the sampling.)
However you would not be able to
- conclude that this is a difference that is not explainable by chance
- conclude that this is not related to the characteristics of the jobs people are doing or the characteristics of the people (skills,
A hypothesis test tries to address the first point under the assumption that the second one is taken care of, which one would typically do with a suitable statistical model (e.g. analysis of covariance on the log-transformed salaries, perhaps with some regularization due to the small population).
Of course, you might also take into account prior knowledge (i.e. use some Bayesian method), given that likely no company is truly that different from others.
What decision you take based on what you see should likely again be based on something else than a hypothesis test, because the cost of wrong decisions either way may be different (e.g. cost of increasing salaries of women if there might be discrimination vs. cost of potential lawsuits and reputational damage). That is something one should rather do with decision analysis than a hypothesis test.