I know it is not politically correct to say it, but I remain unconvinced that gender parity is a desirable goal. Particularly given the current state of research into differences in gender averages.
Here is a real example. Per https://en.wikipedia.org/wiki/Spatial_visualization_ability#... men have about a one standard deviation advantage in spacial reasoning over women. Assuming that both distributions are normal with the same variance, that means that if we pick the top X% of the population on spacial reasoning where X is fairly small, we will get about an 80/20 split of male/female. Within that top group there will be no remaining difference between men and women.
Back in the 1960s there was discrimination and no women were in engineering. This was a terrible waste of talent. But by the late 1980s, women were 20% of engineering students. Decades of hand-wringing later, women are still about 20% of engineering students. Based on spacial reasoning ability, perhaps women SHOULD be about 20% of engineering students.
What happens if we force gender parity? If the research on gender differences is right, selecting on spacial reasoning except making sure to select 50% women would result in a situation where you had 50% men, 12.5% women who are as good as the men, and the remaining 37.5% women who are worse than EVERY man at spacial reasoning. The result is that 3/4 of the women are worse than all the men. Is this a better outcome? Why?
Now I picked an example where men have an advantage. But men don't in all fields though. According to other research, women are better on average at management. This is an argument to accept the data and do our best to hire and promote on competence.
Now that argument applies to hard engineering. It isn't software development. I do not know why the ratio is so extreme in software development. (More extreme than in, say, mechanical engineering.) However I have also never seen data suggesting that sorting on interest and ability shouldn't result in the ratios that we see. Before we double down on equality as a mandate, I would like to see that data collected.
As long as, on average, the men and women you hire are equally good, your hiring process is not broken. If your data finds that there is a difference in average ability, then adjust your practices to get higher average competence. Encourage everyone to have the opportunity. Make it clear that all people with title X are equivalent regardless of secondary characteristics, AND work to make that true. (I believe that it is pretty true today.)