Summary

Experience

Staff Distributed Systems Engineer|Amazon Web Services (AWS)

Seattle, WAMar 2020Present

• Led the design and implementation of a new distributed caching layer, reducing latency by 30% and handling 5M+ QPS across global regions.
• Architected a fault-tolerant data replication service, achieving 99.999% availability and zero data loss for critical customer data.

Senior Software Engineer, Distributed Systems|Microsoft Azure

Redmond, WAAug 2015Feb 2020

• Developed and deployed a highly concurrent message queue service, processing over 1 billion messages daily with <10ms end-to-end latency.
• Implemented real-time data streaming pipelines using Apache Kafka and Flink, improving data processing throughput by 40%.

Software Engineer|Dropbox

San Francisco, CAJun 2012Jul 2015

• Contributed to the core distributed storage infrastructure, enhancing data integrity and availability for 500M+ users.
• Developed and optimized microservices for file synchronization, reducing sync times by an average of 15%.
• Participated in the migration of monolithic services to a microservices architecture, improving system scalability.

Projects

Distributed Key-Value Store

Sep 2018Feb 2019

• Designed and implemented a highly available, eventually consistent key-value store in Go, leveraging a Raft-based consensus protocol.
• Achieved 99.99% availability and horizontal scalability for 1M+ operations per second on commodity hardware.
• Developed a client library with automatic retry mechanisms and connection pooling for improved resilience.

Serverless Data Pipeline Framework

Jan 2021Jul 2021

• Created an event-driven data processing framework using AWS Lambda, Kinesis, and S3 to ingest and transform large datasets.
• Reduced infrastructure operational overhead by 80% compared to traditional server-based solutions.
• Implemented robust error handling and dead-letter queue mechanisms to ensure data integrity during processing.

Real-time Metrics Aggregator

Mar 2016Aug 2016

• Developed a Python-based real-time metrics aggregation service utilizing Apache Kafka for ingestion and a custom time-series database.
• Processed 100,000+ data points per second with sub-second aggregation latency.
• Designed a flexible plugin architecture allowing easy integration of new metric sources and aggregation functions.

Education

Carnegie Mellon University|M.S. in Computer Science

Pittsburgh, PASep 2010May 2012

• Thesis on optimizing scalable consensus algorithms for geo-distributed environments.
• Awarded Dean's Fellowship for outstanding academic achievement and research potential.

University of Illinois Urbana-Champaign|B.S. in Computer Science

Urbana, ILSep 2006May 2010

• Graduated Summa Cum Laude with a GPA of 3.9/4.0.
• Developed a fault-tolerant distributed file system as a senior project, achieving 99.9% availability.

Skills

Programming Languages

JavaGoPythonC++Rust

Distributed Systems

MicroservicesConsensus Algorithms (Raft, Paxos)Distributed CachingMessaging Queues (Kafka, RabbitMQ)Fault ToleranceConcurrency

Cloud Platforms & Technologies

AWS (EC2, S3, DynamoDB, Kinesis, Lambda)AzureDockerKubernetesTerraform

Databases & Storage

NoSQL (Cassandra, MongoDB)Relational (PostgreSQL, MySQL)Key-Value StoresDistributed File Systems

Tools & Methodologies

GitJiraCI/CDAgile/ScrumPrometheusGrafana