Most data problems are language problems.
I know this because I spent years studying language before I ever wrote a pipeline. My PhD is in Hispanic Linguistics — I was trained to notice how organizations use words, how context changes meaning, and how people talk past each other while believing they're communicating. It turns out that's exactly the diagnostic skill you need when a company's data infrastructure isn't working.
After my doctorate, I moved into data engineering and ML consulting. I've built cloud pipelines in Microsoft Fabric, implemented LLM and RAG systems for companies that couldn't yet hire in-house AI teams, and designed decision tools for leadership at firms in New York, St. Louis, and across Spain.
What I bring that most technical consultants don't: I can walk into a room, listen to how a team talks about their data problem, and tell you in thirty minutes whether it's a technical problem, a governance problem, or a communication problem — and which one to fix first.