My Resume
Summary
9+ years of experience
Senior Software Engineer and Technical Lead with over 9 years of experience in designing and developing scalable software systems, APIs, and data-intensive applications. Expertise in Python-based backend development, microservice-oriented architectures, asynchronous processing, and high-performance data engineering. Proven ability to optimize data pipelines, build comprehensive monitoring and telemetry solutions, and lead engineering teams in delivering complex projects.
Skills
Programming
- Python
- C / C++
- Bash / Shell
- JavaScript / TypeScript
- HTML / CSS
- Java
Backend & APIs
- REST APIs & Microservices
- Django
- Flask
- Plotly Dash
- PostgreSQL
- TimescaleDB
- Kafka
- Prefect
- Langchain
- Pydantic
DevOps & Infrastructure
- Docker
- Ansible
- CI/CD (GitHub Actions, Jenkins)
- SLURM
- PBSPro
- HPCM
Education
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Georgia Institute of Technology
Additional coursework in Machine Learning
Online | 2019-2021 -
Washington State University
Bachelor's in Computer Science
Bachelor's in Electrical Engineering
Vancouver, WA | 2012-2016 | GPA: 3.83 -
Lower Columbia College
Associate's in Computer Science
Longview, WA | 2010-2012 | GPA: 3.79
Experience
Intel Corporation
Lead HPC Full-Stack Data Engineer
July 2022 - Present
- Spearheaded architecture, UI/UX design, and development of a Plotly Dash-based data analytics platform and a modular, microservice-oriented backend infrastructure for the Aurora Supercomputer, enabling real-time health monitoring and advanced historical analysis.
- Developed a Prefect-based data pipeline to incrementally process new HPC failure data, transforming legacy batch scripts into a 100x faster, automated workflow.
- Engineered scalable, asynchronous data ingestion systems using Kafka; evolved critical data pathways from REST APIs to event-driven architectures to meet scaling demands for systems with ~10,000 nodes.
- Designed event-based database schemas to correlate system failures with configurations; developed key health indicators and data-driven workflows that significantly improved failure disposition, repair processes, and health reporting to Argonne National Labs.
- Designed an AI-powered system utilizing Langchain and ChatGPT to auto-generate Sphinx documentation for a large monorepo, ensuring seamless integration with ongoing code changes.
- Developed flexible Grafana dashboards for monitoring Aurora telemetry data stored in TimescaleDB, giving mechanical and electrical engineers access to data they need to analyze and solve pertinent hardware issues.
- Automated resource-manager-agnostic HPC system regressions, streamlining the testing process by launching test cycles across both SLURM and PBSPro.
- Established a robust CI/CD pipeline using Docker, accelerating testing and deployment.
- Led and mentored a team of approximately 3 engineers, managed project priorities, delegated tasks, and onboarded new members for a large-scale data monitoring and analytics platform.
DevOps and Validation Framework Engineer
August 2021 - July 2022
- Created a novel resource management plugin for test harnesses, facilitating adaptation to new HPC systems.
- Maintained and resolved issues in an ElasticSearch cluster, ensuring availability of essential system debug data.
- Directed successful migration of repositories and JIRA issues under stringent deadlines, demonstrating leadership skills.
- Enhanced system usage dashboard, bolstering system reliability and data confidence.
BMC Test Infrastructure Engineer
December 2020 - July 2021
- Automated the triage process by auto-generating JIRA issues per unique failure signature, accelerating debug efficiency and improving the test pass rate from 60% to 95%.
HPC Validation Framework Engineer
June 2016 - November 2020
- Main contributor developing a Django-based test automation framework, accelerating development of new test content.
- Designed Ansible configuration for HPC clusters, reinforcing infrastructure reliability by automating installs and backups.
Washington State University
AI Research Assistant
June 2014 - June 2016
- Used Machine Learning Apache Spark to detect powerline faults on 10TB of data with 99.5% accuracy.
- Co-published 5 Machine Learning Research papers, including the "Best Student Paper Award" for Springer.
Personal Projects
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OFTW Data Analytics Dashboard --- Interactive Plotly Dash dashboard analyzing OFTW donation data since 2014, featuring dynamic visualizations, custom filters, and AI-driven insights for exploring donation patterns and fundraising metrics.
Technologies: Plotly, Dash, Python, Vizro, Vizro-AI
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MN Bookkeeping ---
A React based bookkeeping website allowing clients to submit receipts and view financial statements.
Technologies: React, Supabase
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Personal Finance App --- Vue.js, Firebase, and Plaid API, using a webhook to load live data from my bank into a dashboard.
Technologies: Vue.js, Firebase, Plaid API
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Webpage Editor --- React and Firebase app for writing custom web pages with a WYSIWYG text editor.
Technologies: React, Firebase
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Quadtree Photo Stylizer --- A Python CLI and module for generating art from photos using Wand and ImageIO.
Technologies: Python, Wand, ImageIO
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Personal Blog --- Statically-generated Hexo Blog with coding tutorials.
Technologies: Hexo, JavaScript
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Lunar Lander --- Double-DQN Reinforcement Learning with Keras in an OpenAIGym simulation.
Technologies: Python, Keras, OpenAIGym, Reinforcement Learning