Fabio Antunes

Turning raw data into business value. One pipeline at a time. I'm a Senior Data Engineer and GenAI Consultant with a Computer Science background, passionate about building data systems that are not just functional, but genuinely impactful. With hands-on experience designing end-to-end data platforms, I bridge the gap between raw, fragmented data and the insights that drive enterprise decisions. Currently, I work at the intersection of Data Engineering and Generative AI by architecting scalable pipelines, enforcing data quality and governance, and enabling AI-powered capabilities that allow users to interact with structured data through natural language. This includes contributing to a platform where an AI agent combines RAG-based document retrieval with MCP-connected text-to-SQL, making data accessible to anyone, not just technical teams. What I bring to the table: Pipeline Engineering: End-to-end design and deployment using Python, Apache Airflow, Snowflake, AWS, PostgreSQL, and diverse ingestion sources (APIs, SFTP, SharePoint, S3, and more) Cost & Performance Optimization: Delivered a 40% reduction in Snowflake compute and storage costs through strategic pipeline optimization and efficient data modeling GenAI Integration: Built MCP Servers from scratch, developed AI agent workflows, and automated development productivity pipelines using Claude Code Data Governance & FinOps: Implemented governance frameworks and a FinOps culture that balances performance, quality, and cost efficiency Team & Process Leadership: Introduced Agile methodologies to data teams, driving sprint health, effort estimation, and a culture of collaboration I believe great data engineering is invisible, but perceptible. Users shouldn't have to think about pipelines; they should just trust their data. That's the standard I hold myself to. Open to connecting with data professionals, product teams, and organizations looking to make their data truly usable and valuable.