I guess my pithy answer is I've never got tired of learning. Four straightforward steps that you've no doubt heard before, but I can confirm they do the trick:

Establish internal credibility. That is, the confidence to speak credibly on a given subject, be it a platform or tool, a technique, a concept, a prediction. Roll your sleeves up and get dirty coding. Even on-rails tutorials force your brain to make the connection between the concepts and the technical reality. Especially for Big Data and ML/DL workloads. Put this all on a public repo. Search GH for relevant repos, fork them, and code walk them - especially Python/R/Scala scripts. Compete on Kaggle, that's obvious. Answer questions on SO, and attempt to replicate problems you find on SO yourself - this yields a lot of benefits, as most SO questions are edge cases. Join the user communities and help forums for popular platforms and read the newest entries - again, you learn the most from others actually practicing in the space. And still an extremely effective technique is to just directly search for e.g. "Spark shuffle joins" on Google and look for real people with real opinions - that you can then test yourself in an environment. When you've already read the blog post or watched the YouTube video or taken the Udacity course the guy across the table is talking about - you really establish credibility.

Teach others what you know. True trial by fire; share what you've learned. You'll learn how to overprepare, communicate and speak plainly, connect with those different than you in personality, behavior and skill, read rooms, provide feedback, take criticism, and most importantly - you'll really, really learn the ins and outs of the material.

Read voraciously. I skim-consume about 25 books a month using my company's Safari subscription; have built up a pretty good "reading recommender" system of Twitter users, subreddits, aggregators, blogs, etc; And not just technical books - books on business strategy, behavioral economics and psych, industry-specific blogs and journals - if you can't explain what you're doing in terms of risk, dollars, or time, you're doing it wrong. (Also a good life pro tip: download every interesting thing you read into a single repo and put a crawler on top of them. Even if you don't know the answer, you know you've read it somewhere and can retrieve it.)

Learn from others. Reading is great, in-person is better, mentoring is the best. Reach out to everyone in the field. Ask them (like you just did to me) what they're reading, what they did, ask follow up questions, share what you're doing with them. I find keeping a list of "questions you'd like to ask" while you're working through material (especially on industry/business) to be invaluable when you meet someone who can potentially answer them.

These days I spent probably 15-20 hours a week just reading, learning, doing, in prep for the 20-30 hours a week I spend educating, communicating, and (hopefully) selling.

One thing to add: I usually am focusing on 2 things at a time, no more, no less. If you can combine them, even better - learn Kafka for streaming and Grafana to visualize it; learn Azure SQL DW or Redshift for distributed DW and Spark for processing; etc.

My real evolution came when I realized I was happy being the dumbest person in the room, and that curiosity is a superpower.