Summary
Highly accomplished Senior Systems Engineer with over 10 years of experience designing, implementing, and optimizing robust, scalable, and secure infrastructure solutions. Proven expertise in cloud platforms (AWS, Azure), automation (Terraform, Ansible), and CI/CD pipelines to streamline operations and enhance system reliability. Adept at leading cross-functional teams and driving complex projects from conception to successful deployment, consistently achieving significant performance improvements and cost reductions.
Experience
Principal Systems EngineerSalesforce
- 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 EngineerGoogle
- 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 EngineerMicrosoft
- 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
- Developed an open-source Python framework leveraging Terraform and Ansible for automated, multi-cloud infrastructure provisioning.
Kubernetes Cluster Autoscaler for Cost Optimization
- 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)
- 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, BerkeleyMaster of Science in Electrical Engineering and Computer Sciences
- Specialized in Distributed Systems and Cloud Computing
- Published research on container orchestration performance, achieving a 15% improvement in deployment times
University of WashingtonBachelor of Science in Computer Science
- 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