I build fast, reliable backend systems that move real metrics.

Marketing and product decisions were bottlenecked by reporting. Reports were slow to generate and expensive to run, and data was scattered across services with no single source of truth.

Designed and built a central data warehouse plus an ingestion pipeline, then exposed the data through reusable APIs so teams could self-serve instead of rebuilding the same queries.

Invested early in a shared data platform rather than one-off reports. It cost more up front but removed duplicated work across teams and made every later project faster.

The client needed staff to ask natural-language questions over private documents — without sensitive content leaking between users, and without manual data prep for every new file.

Built a retrieval-augmented-generation pipeline: automated ingestion, chunking and embedding into a vector store, with an LLM answering only from retrieved, permission-scoped context.

Made per-user data isolation a first-class part of the design rather than an afterthought, so security held up even as the document set and user base grew.