About
A generalist who has seen every layer
The short version
With over a decade working across every discipline in data, I bring a perspective that most specialists can't — I can build it, analyse it, and explain why it matters to the business.
My background is a blend of mathematics and computer engineering, with graduate degrees from a leading technical university. That combination gave me a deep quantitative foundation and a bias for building things that actually run in production.
What makes me different is that I don't have a specialisation silo. Most data professionals are strong on either the engineering or the analytics side. I am fluent in both — I can design systems that are architecturally sound and analytically meaningful at the same time, and speak the language of every stakeholder in the room.
Credentials
BSc in Mathematics
BSc in Computer Engineering
Career arc
- Data Analyst Global financial services & insurance Quantitative foundations across complex data environments at scale.
- Data Scientist Mobility startup Modelling and experimentation in a fast-paced product environment.
- Data Scientist → Data Engineer Digital health scale-up — startup through IPO Rode 10× hypergrowth in three months, through an IPO and acquisition.
- Staff Data Engineer & Team Lead Data platform ownership Platform ownership, hiring & coaching, exec-level stakeholder management.
- Staff Software Engineer & Tech Lead Platform engineering Data contracts at scale, cross-functional technical leadership.
- Group Technical Product Manager, Data Products Data strategy Roadmap and priorities for a portfolio of data products across engineering, analytics, and data science. Owned the company data strategy.
- Staff Data Developer, Data Excellence AI readiness and adoption Drove AI readiness and AI adoption company-wide, with strong data governance processes and a culture of data excellence.
Why me
Full data lifecycle fluency
From source system ingestion and pipeline engineering to data modelling, analytics, experimentation, and executive reporting.
Proven at every stage of maturity
Built data functions from zero, scaled them through rapid growth, and matured them into trusted, org-wide platforms. I know where the traps are at each phase — including the ones that quietly sink an AI initiative before it starts.
Bridges engineering and the business
Architecture with engineers. ROI with your C-suite. In the same day. That rare combination prevents the misalignment that kills most data initiatives.
Academic depth, practical output
Rigorous by training, pragmatic by experience. The kind of background that shows up in the quality of the work, not just the resume.
Stack
Languages & stores
- Python
- SQL
- Terraform
- Snowflake
- PostgreSQL
- S3
Tools & frameworks
- dbt
- Airflow
- Meltano
- Singer
- FastAPI
- Snowplow
Analytics & BI
- Tableau
- Metabase
- A/B Testing
- Predictive Analytics
Domains
- Healthcare
- FinServ & Insurance
- Mobility & IoT
- SaaS