Summary

Experience

Principal Systems Engineer|Salesforce

San Francisco, CAMar 2021Present

• Led the architectural design and implementation of a new global data replication system on AWS, reducing data synchronization latency by 40% and improving disaster recovery RTO by 50%.
• Orchestrated the migration of critical legacy services to a Kubernetes-based platform, resulting in a 30% reduction in operational overhead and a 20% increase in application uptime.

Senior Systems Engineer|Google

Mountain View, CAJun 2017Feb 2021

• Designed and implemented scalable infrastructure solutions for Google Cloud Platform, supporting over 100 million daily active users and ensuring 99.99% availability.
• Automated server provisioning and configuration management across 5,000+ Linux instances using Ansible and custom Python scripts, reducing setup time by 75%.

Systems Engineer|Microsoft

Redmond, WAAug 2013Jun 2017

• Administered and maintained Windows Server and Azure infrastructure for mission-critical enterprise applications, achieving 99.9% uptime.
• Developed PowerShell scripts to automate routine system administration tasks, saving approximately 10 hours of manual work per week.

Projects

Automated Cloud Provisioning Framework

Jan 2022Present

• Developed an open-source Python framework leveraging Terraform and Ansible for automated, multi-cloud infrastructure provisioning.

Kubernetes Cluster Autoscaler for Cost Optimization

Mar 2020Sep 2020

• Implemented a custom Kubernetes autoscaler that dynamically adjusted cluster size based on predictive workload patterns and spot instance availability.
• Achieved a 25% reduction in cloud compute costs for non-critical workloads by intelligently utilizing cheaper resources.
• Contributed back relevant findings and optimizations to the community-driven Kubernetes autoscaler project.

Distributed Logging Aggregator (GoLang)

Jul 2018Jan 2019

• Engineered a lightweight, high-performance distributed logging aggregator in Go to centralize logs from diverse microservices.
• Improved log processing throughput by 300% compared to previous solutions and ensured reliable data ingestion into Elasticsearch.
• Implemented fault-tolerance mechanisms to prevent data loss during network partitions or temporary service outages.

Education

University of California, Berkeley|Master of Science in Electrical Engineering and Computer Sciences

Berkeley, CASep 2013May 2015

• Specialized in Distributed Systems and Cloud Computing
• Published research on container orchestration performance, achieving a 15% improvement in deployment times

University of Washington|Bachelor of Science in Computer Science

Seattle, WASep 2009Jun 2013

• Graduated Magna Cum Laude with a GPA of 3.8/4.0
• Awarded Dean's List for 6 consecutive semesters
• Developed a peer-to-peer file sharing system as a capstone project

Skills

Cloud Platforms

AWSGoogle Cloud Platform (GCP)AzureKubernetesDockerOpenStack

Automation & IaC

TerraformAnsibleChefPuppetCloudFormationJenkins

Operating Systems

Linux (RHEL, Ubuntu, CentOS)Windows ServerVMware ESXi

Programming & Scripting

PythonBashGoPowerShell

Monitoring & Logging

PrometheusGrafanaELK Stack (Elasticsearch, Logstash, Kibana)SplunkDatadog

Networking

TCP/IPDNSVPNLoad BalancingFirewallsCDN