The spreadsheet itself brings a lot of power to the table. (Pun not intended!)
There are some cool things you can do using spreadsheet expressions, like make random values that change every time you download the CSV sheet, which is great for testing. But expressions have their limitations: they can't add new rows and columns and structures, for example. However, named ranges are useful for pointing to data elsewhere in other sheets, and you can easily change their number of rows and columns.
For convenience and expressivity, I've defined ways of including other named sheets and named ranges by reference, and 2d arrays of uniformly typed values, and also define compact tables of identical nested JSON object/array structures by using declarative headers (one object per row, which I described in the article, but it's not so simple, and needs more examples and documentation).
At which point Terraform has a weak templating engine already, but its generally enough for building reusable infra. Additional features can be provided within the spreadsheet using reusable libraries. One pain point with embedding functional dataprocessing in a spreadsheet for JSON data, is a decent way of writing tree expressions, to which I would turn to the de facto JSON tooling jq for inspiration.
if you want to take this further, I am up for building some infra for continuous deployment spreadhseets through terraform. tom <dot> larkworthy <at> futurice.com
But I would not embed stuff inline with the JSON. I would have a pure sheet dedicated to stuff going in, and a compute sheet for stuff join out. And the definition for stuff going out should basically be a JQ expression, that can "shell out" to sheets expressions https://github.com/sloanlance/jq/issues/1
e.g. calling another google service with the JSON using a token minted BY THE USER CURRENTLY USING THE SHEET