I am a Data Analyst & Engineer with more than a decade of experience across digital analytics, measurement architecture, cloud data engineering and business intelligence.
I enjoy working between technical implementation and business understanding: defining what should be measured, making collection reliable, transforming raw data into useful models and helping people reach clear decisions.
I value curiosity, clear communication, attention to detail and solutions that remain understandable and maintainable after implementation.
Senior Data Analyst & Engineer / Analytics Consultant
Current · Enterprise digital analytics and data engineering
Designing and operating analytics, measurement and data solutions across complex international digital environments.
- Measurement architecture and Google Tag Manager governance
- GA4 and first-party/server-side tracking
- BigQuery data modelling and analytics engineering
- Dataform pipelines and incremental transformations
- Consent, privacy and tracking-quality controls
- Monitoring, anomaly detection and data reliability
- Customer-data activation and event-driven integrations
- Documentation, stakeholder communication and technical guidance
Founder and Data Consultant — Powerful Data
Independent analytics and data consultancy
Helping organisations turn raw digital and customer data into reliable analytics systems. Work includes measurement strategy, technical implementation, BigQuery modelling, reporting, data quality, automation and practical decision-support solutions.
Earlier Digital Analytics Roles
Agency and in-house environments
More than a decade working across analytics implementation, reporting, optimisation and data engineering for organisations ranging from smaller businesses to complex international companies. This experience shaped my belief that good analytics requires more than tools: it requires business context, reliable definitions, technical discipline and communication.
GA4, Google Tag Manager, server-side tracking, consent, measurement architecture and implementation quality.
SQL, BigQuery, Dataform, user/session/page models, incremental pipelines and reusable analytical datasets.
Data-quality controls, monitoring, anomaly detection, naming standards, ownership and documentation.
Reporting, visualisation, business interpretation, activation, conversational analytics and AI-ready data products.
- Analytics Engineering
- SQL
- BigQuery
- Google Cloud Platform
- Dataform
- Google Analytics 4
- Google Tag Manager
- Server-side GTM
- Measurement Architecture
- Data Quality
- Data Governance
- Consent and Privacy
- Customer Data Activation
- Looker Studio
- Tableau
- Python
- R
- AI Agents
- Conversational Analytics
- Football Analytics