I come from a PhD-level background in biomechanics and human movement science. That means I've spent years working with complex, messy data — designing experiments, building models, and extracting meaning from noise.
I now apply that same rigour to business data systems.
- Data Engineering — ELT pipelines, data warehouses, layered data models
- Workflow Automation — Airflow, orchestration, operational efficiency
- Agentic AI — LLM integration, data-triggered agents, AI-assisted processes
- Data Quality — testing, validation, reliable metrics at scale
A PhD trains you to ask the right questions before building anything. I bring that to every project:
- Translating business problems into data requirements
- PhD-level analytical thinking applied to real operational challenges
- Clear communication between technical and non-technical stakeholders
- SMEs & startups — building data foundations from scratch, replacing manual processes
- Large enterprises — freelance missions on data platform design, pipeline architecture, and AI integration
Python SQL dbt Airflow Fivetran Airbyte PostgreSQL BigQuery Metabase Docker