Data platforms, made boring.

I'm a backend and data engineer with 4.5+ years of experience. My job is the unglamorous part of a data platform — making sure the pipelines run, the data is trustworthy, and problems surface before anyone else notices. I like the boring version of a system: predictable, measurable, safe to change.

At TCS in Dallas I work on the batch-operations platform for a Fortune-500 bank. The numbers I'm most proud of: the core batch job went from ~15 minutes to under 1, and the platform now predicts an SLA miss before it happens instead of reporting it after. I also run my own AI stack at home — a 27-billion-parameter language model on a single desktop machine, with an automated pipeline on top where every output is traceable to its source.

What I care about: reliability you can prove (benchmarks, not adjectives), privacy you can verify (data that never leaves a device), and honesty in engineering (catch the defect before it ships, then say so). I hold a master's in IT & Management from UT Dallas.