This is a bit silly way to use LLMs to process tabular data. In reality, you'd ask it to write functions and execute them. First you'd ask it to create a type definition from the table, then ask it to create functions to process the data.

"Write a function to find years of experience by name? Return just the number, e.g. '12'."

It works much better, and it can single-shot many of the processing requirements just from type definitions it can infer from the data.

This way it's easier to stick to tabular formats that have easy reading libraries, like with TypeScript/JavaScript JSON, and with Python, maybe CSV...