§01 About
Dominique is a Principal Software Engineer with 20+ years of experience building and scaling complex product platforms. He translates business strategy into architectural direction and drives technical initiatives across organisational boundaries — without relying on formal authority.
His signature work is a multi-year composable commerce transformation: migrating a Magento monolith to a modern platform built on Spryker, AWS Serverless, and Next.js, with a GraphQL API layer serving as the integration contract across web, mobile, and backend.
He leads through clarity and technical depth, involves himself early in product discovery, and uses AI tools as a core part of his engineering workflow. He is looking for Staff or Principal-level roles in product-led SaaS companies where ownership is real and process is lean.
§02 Work
Case Study · 01
2019–2025
Migration of a large-scale Magento monolith to a modern composable architecture built on Spryker — a six-year platform transformation serving web, mobile, and backend from a single GraphQL contract.
Serverless integration layer on AWS as middleware between on-premise commerce and modern frontends. Lambda, AppSync, and Cognito for secure, scalable, decoupled communication.
Led Test-Driven Development and automated QA practices across a cross-functional team of 12+. Established unit and integration testing as a development standard.
§03 Expertise
Driving architectural decisions across team and organisational boundaries through clarity, reasoning, and trust — not hierarchy. Engineers and stakeholders align because the direction makes sense.
Building systems that enable products, not just products themselves. Stable API contracts, decoupled architectures, and independent deployment capabilities that let teams move fast.
Translating business requirements into scalable technical direction from the earliest stages of product discovery. Reducing the gap between what the business needs and what engineering delivers.
Taking full responsibility for systems from initial concept through implementation, production, and long-term evolution. Not handing off at deployment — owning the outcome.
Using AI tools as a core part of the daily engineering workflow to accelerate delivery, improve code quality, and raise the bar for the entire team — not as an experiment, but as standard practice.
Making complex architectural trade-offs understandable to non-technical stakeholders. Enabling better business decisions by making the engineering reality visible and actionable.