I design and engineer scalable data infrastructure — ETL pipelines, distributed systems, and the platforms that power real-world healthcare and product decisions.
I'm a data and backend infrastructure engineer with a deep love for making messy data into something meaningful. I most recently worked at Aledade on healthcare data pipelines — transforming clinical data at scale into insights that help independent primary care practices thrive. I'm currently exploring new opportunities where I can bring that experience to the next interesting problem.
Before that, I spent time at Google, working across YouTube comment infrastructure, advertising platforms, and ML/robotics systems. I've shipped things that touched millions of people, and I've debugged things at 2am that nobody should have to debug.
When I'm not writing PySpark or arguing with Spark SQL, I'm drawing on my iPad, working on a sci-fi novel, cooking things that require more patience than I have, and keeping my houseplants from dying. I care a lot about the people side of engineering — thoughtful systems design, inclusive teams, and building things that actually matter.
Building and maintaining large-scale healthcare data ETL pipelines processing millions of clinical records. Designing robust data models and Databricks/Spark infrastructure that powers analytics and care delivery decisions for independent primary care practices across the US.
Worked across several teams including YouTube comment infrastructure (serving comment systems at global scale), advertising platforms, and ML/robotics systems. Built distributed backend services and data pipelines impacting millions of users daily.
A personal AI assistant app with intelligent scheduling, conversation memory, and a clean architecture built around a custom SchedulingAgent. Built because existing tools didn't quite fit the way I think.
A tool that ingests exported conversation histories from Gemini, ChatGPT, and Claude and weaves them into a unified dataset — surfacing behavioral analyses and head-to-head comparisons across models.
A Magic: The Gathering cube spanning almost 10,000 cards, brought to life in Tabletop Simulator through custom tooling that keeps the draft pool ever-changing — a different chaotic experience every game.
A hard sci-fi epic in progress, exploring a fracturing society and humanity's evolving relationship with AI. Currently being drafted, chapter by chapter.