Eric Waters
Hi, I'm Eric
I'm a Software Engineer with proven expertise in building robust APIs, data pipelines, AI/ML integrations, responsive UIs, and cloud/DevOps solutions.
Intel Corporation
Software Application Development EngineerAugust 2023 - PresentBuilt a standardized manufacturing ETL platform, delivered 5 enterprise GenAI apps, created a no-code AI studio, and led FastAPI/ML API and enterprise search initiatives.Arizona State University
Computer Science (Big Data Systems), M.S.August 2022 - May 2023Studied Data Mining, Data Processing at Scale, Statistical Machine Learning, Data Visualization, Database Management System Implementation, and Mobile Computing.Dell Technologies
Graduate Software Engineering InternJune 2022 - August 2022Implemented OAuth 2.0 SSO and fine-grained authorization across enterprise apps and REST APIs using Spring Boot and Angular, centralizing authentication and strengthening security and compliance.Arizona State University
Computer Science, B.S.August 2019 - May 2022Studied Data Structures and Algorithms, Programming Languages, Operating Systems, Software Engineering, Database Management Systems, QA & Testing, and various mathematics.Dell Technologies
Undergraduate Software Engineering InternMay 2021 - August 2021Built a custom Kanban board application with Spring, improving agile workflow visibility and collaboration across engineering teams.
Quality Code, Real Results
Over 3 years of professionally building and shipping full-stack applications.
2023 - Present
2023 - Present
Intel Corporation - Chandler, AZ
Software Application Development Engineer
Batch Data Processing Platform
Designed and built a standardized batch processing framework that unifies disparate manufacturing ETL implementations using Airflow, Docker, Kubernetes, GitHub Actions, and ELK.
Created reusable platform tooling for ETL development, logging, CI/CD, and DAG creation, enabling teams to rapidly build and deploy pipelines with consistent infrastructure, performance, and quality.
Generative AI Web Platform
Developed a suite of 5 enterprise GenAI applications using Angular and Python (Sanic), including a legal contract auditing tool estimated to save $30M annually and recognized with a Divisional Recognition Award.
Designed and developed a no-code AI application studio using React, Next.js, and Tailwind CSS, enabling non-technical teams to create custom AI workflows through an intuitive drag-and-drop interface.
Transformed the platform UI/UX into a modern, visually polished experience and built reusable frontend components that improved consistency and accelerated feature delivery across applications.
Autonomous Excursion Response API
Led consolidation of two large-scale FastAPI services into a unified API, standardizing authentication, CI/CD workflows, Kubernetes deployments, and logging, reducing long-term complexity and maintenance overhead.
Factory ML Analysis API
Engineered an asynchronous FastAPI service for internal ML algorithms, enabling external applications to execute long-running analytics jobs and retrieve ranked correlation results from factory-scale datasets.
Designed a blue-green deployment architecture on Windows VMs and automated CI/CD with GitHub Actions, enabling seamless failover and zero-downtime deployments.
AI Enterprise Search Engine
Administered an AI-powered enterprise search platform, developing Python ETL pipelines and managing 4 VMware servers to index millions of manufacturing documents and unify fragmented knowledge sources.
2022
2022
Dell Technologies - Round Rock, TX
Graduate Software Engineering Intern
Implemented OAuth 2.0 SSO and fine-grained authorization controls across multiple enterprise web applications and REST APIs using Spring Boot and Angular, centralizing authentication, strengthening security and compliance, and streamlining user access.
2021
2021
Dell Technologies - Round Rock, TX
Undergraduate Software Engineering Intern
Built a custom Kanban board application using Spring, improving agile workflow visibility and collaboration across engineering teams.
Academic Excellence
Rigorous study in computer science and engineering principles.
Computer Science, M.S.
Big Data Systems ConcentrationArizona State University2022 - 20234.0 GPA
Overview
Focused on designing and deploying scalable systems for processing and analyzing large-scale, complex datasets. Gained hands-on experience with distributed computing, real-time data processing, data mining, machine learning, and visualization through project-based learning—equipping me to develop efficient, data-driven solutions across various domains.
Key Coursework
- Data Processing at Scale
- Data Mining
- Semantic Web Mining
- Statistical Machine Learning
- Data Visualization
- Knowledge Representation
- Mobile Computing
- Database Management System Implementation
Computer Science, B.S.
Arizona State University2019 - 20224.0 GPA
Overview
Studied the design, development, and analysis of software systems, building a strong foundation in programming, data structures, algorithms, and computer systems. Gained hands-on experience in machine learning, cybersecurity, and software engineering, developing the skills to solve complex technical problems and build robust, scalable applications.
Key Coursework
- Programming Languages
- Object-Oriented Programming & Data Structures
- Data Structures & Algorithms
- Database Management
- Machine Learning
- Software Engineering
- Operating Systems
- Information Assurance
- Software QA & Testing
- Probability & Statistics Engineering Problem Solving
- Theoretical Computer Science
A Powerful Toolbox
Robust, relevant, and always evolving.
Programming Languages
TypeScript
A superset of JavaScript that adds static typing. I use it in all my web projects, as it helps catch errors early and improves code quality.
Python
A versatile language that I use extensively for data analysis, web APIs, machine learning, and one-off automation scripts.
Java
A high-level OOP language that was my first. I used it throughout high school, college, and in my internships to build everything from command line tools to web applications.
C/C++
A low-level language that I used in multiple college courses for learning principles of programming languages, data structures, and algorithms.
C#
Microsoft's object-oriented language. I've used it for Unity game development and an Intel desktop application.
SQL
A language for managing and querying databases. I studied it formally in several database courses and use it very frequently in my work as an owner of several relational databases.
Web Development
React
A JavaScript library for building user interfaces. I've built multiple applications using React, including this website. It's my go-to library for web development.
Angular
A comprehensive framework for building web applications. I've used it extensively at both Intel and Dell. I appreciate its batteries-included approach and dependency injection system.
Tailwind CSS
A utility-first CSS framework for rapidly building custom user interfaces. I use it in most of my web projects, including this website. It drastically improves my productivity and design consistency.
Next.js
A React framework for building full-stack web applications. I've used it for multiple projects, including this website. I love its performance, file-based routing, and server actions.
Spring
A Java-based framework for building enterprise applications. I used it in both my Dell internships to build web applications and REST APIs.
Laravel
A PHP framework for building web applications. I used it for a year-long capstone project where I built a full-stack contractor management system.
FastAPI
A modern web framework for building APIs with Python. I used it at Intel to build a high-performance API for running machine learning analysis jobs.
Sanic
A Python web framework optimized for speed and asynchronous APIs. At Intel, I used Sanic to build scalable, low-latency endpoints for serving generative AI models in production.
OAuth 2.0
An open standard for access delegation. I've used it in multiple projects to implement secure authentication and authorization flows.
D3.js
A JavaScript library for producing dynamic, interactive data visualizations in web browsers. I learned it formally in a graduate data visualization course and built many highly interactive custom visualizations.
Data Technologies
Apache Airflow
An orchestration platform for scheduling and managing ETL workflows. At Intel, I built an internal Offline Analytics Platform around Airflow DAGs to standardize and improve data pipelines.
Pandas
A powerful Python library for data manipulation and analysis. I used it extensively in graduate school and at Intel for data cleaning, transformation, and analysis tasks.
NumPy
A fundamental package for scientific computing with Python. I used it in graduate school for numerical computations and data manipulation, especially in conjunction with Pandas.
Matplotlib
A plotting library for Python. I used it in graduate school for data visualization tasks, creating static, animated, and interactive visualizations in Python.
Kafka
A distributed event streaming platform. I used it in a graduate school project as the foundation of a data pipeline to stream taxi trip data into Neo4j.
Spark
A distributed data processing engine. I used it in a graduate school project to build a data pipeline for batch processing of large-scale datasets stored in Hadoop.
Hadoop
A framework for distributed storage and processing. I used it in a graduate school project to implement MapReduce algorithms for processing large distributed datasets.
Neo4j
A graph database management system. I used it in a graduate school project to model taxi trip data and apply the PageRank algorithm to identify high-traffic routes.
SQL Server
Microsoft's enterprise relational database. At Intel, I managed and analyzed millions of records, using its security, high availability, and Microsoft integration features.
PostgreSQL
A leading open-source relational database. I used it in academic and professional projects for structured data, leveraging its lightweight setup and JSON support.
MySQL
A lightweight and simple relational database. I've used it in many personal projects and at Dell for building web applications, appreciating its ease of setup and efficient performance.
ML/AI Tools
TensorFlow
A platform for building and deploying ML models. I used it extensively in graduate school for various ML tasks and leveraged TensorFlow Lite to deploy models on mobile devices.
Scikit-learn
A Python library for machine learning. I used it in graduate school for various ML tasks, including classification, regression, and clustering.
Keras
A high-level neural networks API. I used it in graduate school for building and training deep learning models, especially for image classification tasks.
DevOps & Cloud
Docker
A platform for developing, shipping, and running applications in containers. I've studied it academically and used it professionally to ensure consistent environments across development, testing, and production.
Kubernetes
An open-source system for automating deployment, scaling, and management of containerized applications. I've studied it in graudate school and used it at Intel to orchestrate containerized applications in production environments.
GitHub Actions
A CI/CD tool that allows you to automate your software workflows. At Intel, I built my own workflows from scratch to automate testing, deployment, and other tasks in several projects.
Rancher
An open-source platform for managing Kubernetes clusters. I've used it at Intel to deploy and manage containerized applications across multiple clusters.
Harbor
An open-source cloud-native registry that stores, signs, and scans content. I've used it at Intel to manage and secure container images in my projects.
ELK Stack
A powerful suite for search, logging, and analytics. I've used it at Intel to create dashboards and alerts to monitor and analyze application performance.