theodore@portfolio:~$ whoami

Theodore
Dyer

Software Engineer II · Data @ IntusCare

I build data pipelines and ETL systems for healthcare and AI/ML. Currently shipping infrastructure for PHI datasets; previously at Apple working on data for Siri and ML teams.

About me

Theodore Dyer

I'm a software / data engineer who builds the pipelines and infrastructure that make ML and analytics possible. My career has spanned healthcare data, big-tech AI infrastructure, and medical device data systems.

These days I'm at IntusCare, building ETL for complex PHI datasets with dbt, Airflow, and Airbyte. Before that I spent a year and a half at Apple on AI/ML data ops — leading a multi-format booking-data pipeline and designing automated PII detection across 12+ locales.

Off the clock I'm usually surfing, rock climbing, or hanging out with my dog Ghost. Lately I've been teaching myself game development in Godot.

San Diego, CA MS — Johns Hopkins BS — UCSC

Where I've worked

  1. Software Engineer II · Data @ IntusCare
    Apr 2025 — Present
    Providence, RI · Remote
    • Build and maintain ETL pipelines for complex PHI datasets using dbt, Airflow, and Airbyte.
    • Analyze and streamline existing early-stage startup processes to reduce tech debt and minimize bugs.
    • Close collaboration with product and web teams to define pipeline requirements and customer data needs.
    • Mentor junior engineers and overhauled the technical onboarding process.
    stack: Python · SQL · dbt · Airflow · Airbyte · Terraform · Grafana
  2. AI/ML Data Engineer @ Apple
    Oct 2023 — Apr 2025
    San Diego, CA · Contract via Inspyr Solutions
    • Led architecture and development of a complex ETL project for multi-format booking data supporting ML teams.
    • Designed automated global PII detection using the Gemini API and custom prompts to reliably flag sensitive information across 12+ locales, decreasing manual PII flagging by graders by approximately 95%.
    • Documented full project architecture and feature roadmap; used it to onboard and lead two engineers for continued development.
    • Overhauled database architecture, redesigned schemas, and handled data migration for Siri benchmarking labs, automating transcription pipelines and reducing manual testing overhead across worldwide lab sites.
    stack: Python · SQL · LLMs · Docker · Airflow · AWS (S3, Glue) · Git
  3. Data Engineer @ Quidelortho
    Dec 2022 — Oct 2023
    San Diego, CA
    • Solely orchestrated the design, development, and deployment of a complex medical data system — automated ETL pipeline, data modeling, and a secure Flask web app for data interaction.
    • Managed full project lifecycle: tech stack selection, system architecture, version control, unit testing, Azure DevOps setup, and Azure cloud cost optimization.
    stack: Azure (Logic Apps, Cosmos DB, Functions) · Python · Flask · Docker · Git
  4. Software Engineer Intern @ Humanyze
    Mar 2021 — Jul 2021
    Boston, MA
    • Reengineered the existing company data pipeline using PySpark and S3 to address PostgreSQL scaling issues for larger clients.
    stack: PySpark · Amazon S3 · EMR · PostgreSQL · Git
  5. Data Science Intern (Lead) @ OpenPath
    Nov 2020 — Mar 2021
    Irvine, CA
    • Led standup meetings and contributed to e-commerce data standardization and fraud detection projects.
    stack: SQL Server · Python · Pandas · scikit-learn · Tableau

Education

Johns Hopkins University
M.S. Computer Science — AI/ML focus
2020 — 2022 · GPA 3.85
University of California, Santa Cruz
B.S. Computer Science
2016 — 2020

Tools & tech

Programming
Python SQL CUDA C++ JavaScript HTML / CSS Bash
Data & Pipelines
Airflow dbt Airbyte PySpark Mage Pandas NumPy Tableau
Databases & Storage
Snowflake PostgreSQL MySQL MongoDB Azure Cosmos AWS S3 Azure Blob Data modeling
DevOps & Cloud
Docker Git Terraform Grafana CI/CD GitHub Actions Pytest Linux Azure Functions Logic Apps AWS Glue EMR
ML & AI
LLMs Gemini API Prompt engineering scikit-learn PyTorch TensorFlow
Leadership
Mentoring Onboarding Sprint planning Stakeholder comms Requirements gathering Code review Documentation

Selected work