I'm a data engineer and scientist with deep expertise in building secure, scalable, open-source data science platforms for government. My background spans from bicycle mechanics to machine learning and advanced data systems, bringing a craftsman's approach to digital infrastructure. I specialize in Kubernetes, data engineering, and machine learning to create tools that serve, not rule, with a focus on developing solutions that prioritize user autonomy and digital sovereignty.
My Journey
My journey from bicycle repair in Toronto to data engineering has taught me that the best solutions come from understanding systems deeply - whether that's the mechanical systems of a bicycle or the complex architectures of cloud infrastructure. This hands-on experience with both physical and digital systems informs my approach to technology: prioritize maintainability, understand the fundamentals, and build for longevity.
Current Focus
I work on cross-functional teams building government-wide, open-source data science platforms using Kubeflow, Kubernetes, and JupyterLab. My work centers on:
- Architecting scalable, secure infrastructure for reproducible ML workflows
- Developing machine learning pipelines and MLOps practices
- Mentoring developers in GitOps, CI/CD, and ethical data practices
- Championing open-source adoption within federal constraints
- Building platforms that empower teams to do their best work
Philosophy
I believe in tools that teach rather than obscure - systems that reward curiosity with understanding rather than locking users into black boxes. Whether it's Kubernetes, bicycle mechanics, or traditional healing arts, I've found that the most valuable skills are those that compound over time, offering deeper insights as you invest in understanding.
My approach combines technical rigor with a human-centered perspective, rooted in collaboration, transparency, and resilience. I lead by enabling rather than controlling, building infrastructure that empowers teams while maintaining focus on long-term sustainability and ethical practices.
Technical Expertise
- Platform Engineering: Kubernetes, Kubeflow, JupyterLab, Docker
- Data Engineering: Pipeline design, reproducible workflows, SAS migration
- Machine Learning: MLOps, model deployment, ML pipelines
- Infrastructure: Cloud platforms (AWS, GCP, Azure), GitOps, CI/CD
- Languages: Python, R, Golang, SQL
- Specializations: Open source advocacy, digital sovereignty, ethical data governance
Anatomy & Physiology
Understanding the human body as a system—its structures, functions, and interconnected pathways. Resources I recommend:
- OpenAnatomy - Open source anatomy resources
- YoSan University Open Access - TCM and integrative medicine resources
Traditional Chinese Medicine
TCM offers a holistic view of health—qi, meridians, and the balance of yin and yang. A practice of listening to the body.
- AIM Academy - Acupuncture and Integrative Medicine Academy, Toronto (where I studied Shiatsu)
Bicycles
Where mechanical intuition meets the road. Steel frames, hand-built wheels, and the simple joy of human-powered travel.
- U Cycle - Toronto bike shop
- Parliament Cycle - Toronto bike shop
Martial Arts
Embodied practice. Discipline through movement. The dojo as a mirror.
- Naka Ima Aikikai - Aikido
- Tai Chi Toronto - Tai Chi
- Toronto BJJ - Brazilian Jiu-Jitsu
Open Source Learning
Resources for the self-taught and curious:
- Linux Journey - Learn Linux at your own pace