Manifold · Data Engineer
Engineering across research and production
At Manifold, I stepped into unfamiliar client teams and took ownership of data problems spanning research and production. My starting point was the context: what users were trying to accomplish, why the system behaved as it did, and what a change would mean for the people depending on it.
Research context
For genomics researchers, the need was to make accumulated experiment and informatics metadata usable alongside new work. I brought historical and incoming sources into a shared, stable model, giving the team a consistent foundation as research continued.
Production responsibility
On a feedback pipeline running 24/7, an upstream column addition meant more than updating a schema. New calculations needed to use the data while downstream consumers still needed their existing contract to hold. I took responsibility for working through those dependencies, communicating the implications, and adapting the processing without breaking that contract. The solution had to work for the teams relying on the pipeline and the production decisions it supported.