I think this definition of "data intuition is a resilience to misleading data and analyses" is an elegant attempt to describe a notoriously fuzzy concept. Well done to author on this one. As a trained teacher, I believe this is one of those soft skills (or aspects of tacit knowledge) that is notoriously difficult to teach or train someone.

I often say to people that the difference between an average person and an expert is that an expert knows which shortcuts/compromises you can make that will only have a small effect on the outcome, and which shortcuts will come back and to shoot you in the foot (and thus should be avoided from the outset). I like that the author's concept of data intuition neatly covers this scenario.

One might say that the author's definition is a negative definition, inasmuch as it is the ability to identify/avoid mistakes, but I think an equally important component of data intuition is the (positive) ability to identify implicit strengths and insights within the data (or data processes) that is presented.

I believe this skill is also very closely related to the ability in identifying which paths of data/statistical/scientific exploration are more likely to produce results than others. And as other commenters have said, this in turn is related to the ability of 'second-order thinking'. That is, connecting the dots where the there is no obvious or explicit connection.

As the saying goes, "sophistication is subtle".