Skills & Technologies

dbt drives the transformation layer of my data warehouse work. My movie analytics ETL project models 176M+ IMDb records into a Kimball star schema with staging and marts layers, backed by 30+ data-quality tests.

PostgreSQL is my primary data store for both warehousing and applications. I design dimensional models for analytics warehouses and normalized schemas for services like CS2 Analytics.

I use SQLAlchemy to define relational models and queries in my Python services, keeping database access and schema management clean across ingestion pipelines and APIs.

My core library for data wrangling in ETL pipelines. I use it to clean, reshape, and prepare large datasets before loading them into PostgreSQL.

I use BeautifulSoup for web scraping and HTML parsing to extract structured data from web pages for ingestion pipelines and data collection projects.

Python is my primary language for data engineering. I use it for ingestion pipelines, ETL jobs, and the FastAPI services that serve the results, including the CS2 Analytics pipeline with its Typer-based CLI.

SQL is the foundation of my data work. I write analytical queries, design dimensional and normalized schemas, and build dbt transformations across staging and marts layers.

I use Java with Spring Boot for backend services, including the API behind this portfolio site. I lean on its strong typing and mature tooling to keep services well-tested and maintainable.

TypeScript keeps my React frontends type-safe and maintainable, including the CS2 Analytics dashboard and this site.

FastAPI powers my Python APIs, including the live CS2 Analytics service and the in-development FreightFolio backend with its AWS Cognito auth.

Spring Boot runs this portfolio's intentionally lightweight Java 21 REST API, with test coverage and CI on every change.

I use NumPy for efficient numerical computation and vectorized operations when transforming and analyzing datasets.

I use scikit-learn to prototype regression, classification, and clustering models, applying training from my graduate data science and machine learning coursework.

I use Jupyter Notebook for exploratory data analysis and for validating datasets during pipeline development.

My framework of choice for creating modular, responsive UIs. I use it for the CS2 Analytics dashboard and this portfolio site.

Used for rapid UI prototyping and design consistency. I apply it to build minimal, professional web layouts efficiently.

Modern build tool I use for fast React development with hot module replacement and optimized production builds.

I containerize services for reproducible environments and consistent CI/CD, including Dockerized Postgres for FreightFolio's per-service databases and migrations.

I use AWS Cognito for production-grade authentication in FreightFolio, with JWKS caching, key rotation, and RS256 token verification. Expanding skills with S3, Lambda, ECS, and RDS for full-stack deployments.

I automate tests, builds, and deployments with GitHub Actions, including CI for CS2 Analytics and a twice-daily QA suite that monitors this site.

Used for version control and collaboration across all projects with branching and PR-based workflows in GitHub.

I use Pytest for unit and integration testing, including 137 automated tests on CS2 Analytics and the Playwright + Pytest QA suite that checks this site twice daily.

I use Playwright for real-browser automation in my QA work. It drives site-sentry's smoke, navigation, and UI checks against kyledarden.com on a twice-daily schedule.

I use Postman to test, document, and automate RESTful API requests and workflows during backend and data service development.