Wesley Schrauwen

Designed and implemented the technical and UX/UI foundations of a fintech accounting automation SaaS product, building the application with TypeScript, Node.js, React, and PostgreSQL, and implementing integrations with Xero, Sage, and QuickBooks Online.

Volunteered to rebuild a legacy metrics system and migrate its data from MongoDB to PostgreSQL on AWS, and collaborated with the Head of Engineering on Docker adoption, AWS usage, faster test execution, and SLO metrics.

Worked on global distribution of client images, videos, and audio to advertising platforms, focusing on availability, consistency, latency, and cost at petabyte scale. Established and led a team for real-time in-app messaging and worked on reliability improvements and a new rendering system.

Led engineering teams of approximately 12 engineers and a data science team of approximately three people, balancing product and technical priorities across sales, company leadership, engineering, and data science.

Worked on a government education project using machine learning to help improve school pass rates, using Python, Spark, and Hadoop to refine ETL pipelines and build data warehouses in Azure. Moved into a team lead role, collaborating with government officials and contractors.

Implemented Linux-based embedded software features to monitor data usage on routers and low-Earth-orbit satellite systems, and aggregated usage data into monthly reports for customer billing and revenue tracking.

Co-founded and subsequently sold a cleaning marketplace connecting households with cleaners, building the backend and Android/iOS applications and designing the user experience and interface.

Owned search functionality across the iOS application and C# backend, using Swift and Objective-C on mobile.

Worked with designers to refine client user flows and identify inconsistencies in UI/UX and branding.

BSc in Financial Statistics from Stellenbosch University.

Machine Learning course offered through Coursera.