10x throughput · Kafka · 13 social channels · built for viral-scale message bursts

Redesigned an enterprise social platform's data layer into an event-driven architecture on Apache Kafka, ingesting and analysing real-time social data from 13 channels.

Sized for viral-scale bursts of 250–1,000 messages/minute per customer, with hybrid delivery paths: streaming (~15–20s average latency) and polling (~2 min), with a worst-case 5-minute latency ceiling.

Also set architecture standards across application, data, and AI, and rebuilt the React/TypeScript frontend for multilingual workspaces with automated WCAG 2.2 / ADA Section 508 accessibility checks. End-to-end throughput improved 10x. Confidential client engagement.