David Felipe Vanegas Ramírez

Advanced Data Engineer @ Loka

About

David is a data engineer at Loka, where he designs and maintains data platforms on AWS for clients across multiple industries. With nearly five years of experience, his day-to-day work revolves around Apache Iceberg, PySpark, Airflow, and production lakehouse architectures. He holds AWS and Databricks certifications and has recently explored the intersection of data engineering and AI agents, building personal tooling on top of the Anthropic SDK. Based in Bogotá, he believes there is a shortage of practical Spanish-language technical content on modern data engineering.

Workshop

Artificial IntelligenceData ScienceCore Python

From S3 to AI Agent: Your First Queryable Lakehouse

FORMAT: WorkshopLEVEL: IntermediateLANGUAGE: Spanish

AI agents are only as good as the data they can query. Most agents built today connect to outdated CSVs, unstructured databases, or nothing at all. What if your agent could query a real lakehouse—with versioning, schema evolution, and time travel—using natural language? In this workshop we build exactly that from scratch using only open-source tools that run on your laptop. Starting from a local Docker Compose stack, we stand up a functional lakehouse with MinIO as S3-compatible storage, Apache Iceberg as the table format, Project Nessie as a Git-like versioned catalog, and Trino as the SQL query engine. On top of that, we build a Python MCP server that exposes Iceberg tables as tools for an AI agent, and connect Claude so it can query the lakehouse in natural language.

David Felipe Vanegas Ramírez

Advanced Data Engineer @ Loka

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