An example is the National Science Foundation NEON project, which is a long-term ecological monitoring initiative with common field methodologies across 81 North American sites. https://www.neonscience.org/
You should be able to publish data as a paper and get academic credit for doing that. Then others can publish analyses of that data, crediting you.
I will add that funding can complicate things a bit, funding sources often get wowed by more "advanced" methods, while the underlying science might be less than stellar. There are important questions that can be answered by small, elegant field studies, and there are questions that require larger datasets and more computation. When we start putting the methodological cart before the scientific horse, that's where we run into problems.
The 'computer scientist' quote illustrates a frustrating trend: tech-centric 'drive-bys' that lack the ecological context required for good science. On the flip side, the 'old guard' who ignore modern data assimilation are leaving massive potential on the table. The field is rightfully shifting from site-specific anecdotes to foundational, broad-scale work, but we need both skillsets to do it justice.