If AI already writes your pipeline, what does the market expect from you?
How data work changes, where the value moves and which skills to learn. The session is in Spanish.
We'll send you the session link and, afterwards, the recording.
What we'll cover
- The fear: will AI replace you? What the industry numbers say.
- How the work changes: from writing the SQL and the DAG to specifying, reviewing, testing and deciding.
- The skills that gain value, one by one, and the ones that lose it.
- Two examples: the job that runs twice and duplicates data without an error, and the 12-tool stack that only needed 4.
- How to work with AI at your side without losing control of what reaches production.
- Your roadmap: the headlines to update your profile and where to start, depending on your background.
- Live Q&A: bring your question.
What goes down and what goes up in value
Down ↓
Writing SQL from scratch
Up ↑
Modeling: which table, which grain, which history to keep
Down ↓
Writing the load script
Up ↑
Making it safe to run twice without duplicating anything
Down ↓
Knowing every tool's syntax
Up ↑
Deciding what goes into the stack and what doesn't
Down ↓
The job finishing green
Up ↑
The number that arrives being the right one
In Joe Reis's 2026 State of Data Engineering, only 11% say their data modeling works well. See the survey →
It's for you if
- ✓ You're an analyst or backend dev who wants to move into data.
- ✓ You already work with data and feel AI changed your job.
It's not for you if
- ✕ You want to learn to build a chatbot, RAG or agents.
- ✕ You want a tutorial on a specific tool.
Who's teaching
Lucas Trubiano. He designs and builds data platforms for banking and financial services, and teaches data engineering and cloud at Trubi Data.
Thursday, Nov 19, live and free
If you can't make it live, sign up anyway: you'll get the recording afterwards.
We'll send you the session link and, afterwards, the recording.