Mr. Tejas Pravinbhai Patel

Engineering Resilient and Scalable Data Systems for Global Applications

Abstract:

In a world where every click, transaction, and interaction depends on data, building systems that are both resilient and scalable is more critical than ever. From startups to global enterprises, the same challenge emerges — how do we ensure our systems stay fast, reliable, and secure, even as millions of users connect from across the world?
In this keynote, Tejas Pravinbhai Patel explores the essential engineering principles behind modern distributed data systems. The session highlights how to design architectures that anticipate failure, adapt automatically, and deliver consistent performance at scale.

Through practical insights and real-world lessons, attendees will discover how partitioning, caching, observability, and regional isolation come together to form the backbone of high-availability systems. The talk concludes with a forward-looking view of how AI, automation, and intelligent design are shaping the next generation of global data infrastructure.

Whether you’re a student, researcher, or industry professional, this session will inspire you to think about data systems not just as code, but as living ecosystems designed to survive, evolve, and perform globally.

Profile:

Tejas Pravinbhai Patel is a Software Development Engineer at Amazon, specializing in distributed systems, data reliability, and large-scale backend architecture. With extensive experience in multi-region data replication, caching frameworks, and high-availability designs, Tejas has engineered systems that handle millions of transactions with predictable performance and fault tolerance. His work emphasizes scalable architectures, observability-driven reliability, and adaptive data systems that enable businesses to deliver globally resilient applications.

Recognized for his deep technical leadership, Tejas has contributed to initiatives that advance cloud-scale data engineering, regional resilience strategies, and system performance optimization. His research and engineering interests include DynamoDB-inspired data models, caching optimization, cross-region replication, and proactive reliability design—areas that directly shape how modern platforms sustain availability and speed under global load.

Tejas’s thought leadership has been featured in global technology conferences, research summits, and innovation programs, where he advocates for a future where resilience, scalability, and intelligent automation form the foundation of every engineering decision. His work continues to bridge practical system design with forward-looking reliability engineering, inspiring developers worldwide to build systems that endure and evolve at scale.