New York, New York, United States
• Architected a scalable event processing framework that dynamically routed traffic between real-time and delayed pipelines while maintaining continuous ingestion for downstream services, reducing message recovery time by 92%.
• Improved processing throughput by 16× by enabling multiprocessing support for Python consumers
• Built a cost attribution platform decomposing cloud spend by product pillar, service, and team, enabling $500K+ annual savings through granular visibility and accountability.
• Developed a Kubernetes deployment framework that allowed teams to define and manage pipelines in code, accelerating development velocity by 90% across monolith subservices.
• Delivered a Kafka management platform providing self-service topic lifecycle management, configuration enforcement, and operational visibility, improving deployment velocity by 91%.
• Scaled ingestion pipeline throughput by 4× and instrumented component-level metrics to track end-to-end event conversion rates.
