The only solution I found working is to leave data field and get back to software one (within same org or not).
No other reliable and meaningful way.
Nothing beats actual job in improving a complex skill. There is no shortcut to imitate that.
I agree with this. At some point you need to work on a hard project, with minimal support, for an extended period of time. The skills you'll learn will be indispensable. Open source can help, but it's hard to replicate being immersed in a difficult role for 40 hours per week.
The more important thing is that you have a genuine interest in the field, which should take you where you need to go. But without at least a small amount of hard software experience you'll be stuck at an intermediate level.
This. I've been in a similar situation working as a data scientist for 2.5 years and went back to software engineering a couple of years ago.
I'm not trying to say that data science and analytics are necessarily bad environments; I just came to realize that I had different expectations for my work than my organization.
While the skills of a software engineer — e.g. quickly comprehending technical references, operating APIs, ability to type more than three lines of code straight — are highly valuable for a data analyst to be productive, I had to realize that my organization did not appreciate the craftsmanship of producing code as much as I still do.
Over time, I had to witness my analyses end up on slides or in Excel workbooks, only to be looked at once. They'd done their job and weren't needed anymore. I was effectively "prompt completing" analytic requests from management to understand the organization/business/whatever better — always with the same result for "my work".
Providing an organization with the intelligence to understand their business is for sure not a bad motivation and can be fulfilling. It's just not a good fit if — instead of the analytics — you consider the software you create for the analytics as your work.