Sushma Vunnam.

I've always been drawn to bringing structure to complexity — whether that's organizing an event where every detail needs to fall into place, or building a data pipeline where every record needs to land exactly where it should.

Outside of work, I enjoy planning and hosting events — decorating, organizing, making sure everything comes together smoothly. There's something deeply satisfying about starting with a blank space and a lot of moving pieces, and ending with something that just works. I didn't realize it at the time, but that's exactly the mindset that makes a good data engineer.

It started at Accenture, where my work involved handling large datasets and cleaning messy, inconsistent data. I found myself genuinely enjoying it — not just the technical side, but the idea that clean, well-structured data actually helps people make better decisions. That realization pushed me to pursue a Master's in Data Analytics Engineering at George Mason University, where I built a deeper foundation in data modeling, distributed systems, and applied machine learning.

Today, at Walmart Global Tech, I design and maintain the pipelines that teams across supply chain, forecasting, and personalization depend on. I work across the full stack — ingestion, transformation, validation, and delivery — processing 100M+ daily records with a focus on reliability and accuracy.

What drives me isn't just the engineering. It's the moment a stakeholder looks at a dashboard and finally understands something that used to feel opaque. It's another team moving faster because a pipeline I built just works. That intersection of solid infrastructure and real business impact is where I do my best work.