Halving AWS Lambda Costs with Python Parallel Processing
A practical guide to optimising Lambda compute time and costs through parallel processing techniques.
Background
I've spent the last decade helping organisations make better use of their data. My work sits at the intersection of strategy and implementation - I can define a data roadmap, but I'll also build the pipelines and dashboards myself.
I've led data teams, built platforms from scratch, and delivered projects across HealthTech, entertainment, sports analytics, and consumer research. I'm comfortable presenting to boards and equally comfortable debugging SQL at midnight.
Outside of data, I serve as a school governor at Dundonald Primary and as Non-Executive Chairman at Conbrako Engineering, a family manufacturing business.
University of Cape Town
Business Science (Marketing)
London, UK
Available for contract work
and advisory roles
Experience
Built the data function from scratch at this HealthTech scale-up. Designed and implemented a modern data stack (AWS, Snowflake, dbt, Omni), grew the team from 1 to 3, and delivered analytics automation that replaced 7 FTE worth of manual processes.
Developed AI-powered customer service tooling that now handles 50%+ of inbound queries. Reduced SLA response times from 24 hours to 10 minutes.
Led data strategy for a spatial analytics platform serving premium sports and entertainment clients including Sky, NFL, F1, Formula-E, and LA Rams. Built visitor heatmaps, dwell-time analytics, and customer segmentation models.
Developed a benchmarking product that generated £150k ARR. Reduced report preparation time by 90%.
Led analytics across the international cinema business. Built ML-powered staff scheduling (4% labour reduction, 5% utilisation increase), competitor price intelligence via web scraping, and merchandise optimisation (20% margin improvement).
Reduced reporting cycles by 75% through automation.
Founded InfoQlik, a data consultancy focused on analytics automation and BI implementation. Prior to that, worked at Nielsen in the analytics division, cutting my teeth on large-scale consumer and media data.
Technology
Case Studies
A practical guide to optimising Lambda compute time and costs through parallel processing techniques.
Data-driven analysis of the factors that influence Airbnb search rankings, with actionable insights for hosts.
Deep dive into listing optimisation based on empirical data collection and statistical analysis.
Rebuilding a fragmented analytics stack into a governed, self-serve platform for clinical teams.
Improving forecast accuracy and stock availability with a modern data pipeline.
Detecting runaway cloud spend with automated anomaly detection and real-time alerts.
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Contact
Open to discussing data strategy, platform builds, and advisory work. Based in London, available remotely.