Senior Lead Software Engineer – Full Stack, Retail Solutions

Responsibilities

• Lead the design, development and operation of new capabilities across our SaaS products.
• Make architectural decisions that balance immediate business needs with long‑term scalability and maintainability.
• Work closely with product, engineering and business leadership to shape product roadmaps and technical strategy.
• Identify and drive improvements across performance, reliability, scalability, security and developer experience.
• Champion modern engineering practices, including AI‑assisted development tools such as GitHub Copilot.
• Lead the adoption of new patterns, frameworks and platform capabilities across teams.
• Mentor engineers and foster a culture of continuous learning, operational excellence and high‑quality delivery.
• Partner with platform, security and compliance teams to ensure our products meet organisational and regulatory standards.
• Contribute directly to production code and remain deeply involved in technical implementation.

Requirements

• 7+ years of software engineering experience
• Experience as a Senior Engineer, Lead Engineer, Staff Engineer or Software Architect
• A degree in Computer Science, Engineering, Data Science or a related field (preferred but not essential)
• Certifications such as Azure Solutions Architect or CKA (beneficial but not required)
• Experience working in consulting or client‑facing environments (helpful but not essential)
• Building and operating modern full‑stack applications using technologies such as JavaScript/TypeScript and Python
• Frameworks such as Express.js, Vue.js, Flask and Pandas
• Designing distributed systems, service‑oriented architectures and microservices
• Cloud‑native development, ideally on Azure Kubernetes‑based platforms and deployment practices AKS and supporting technologies such as ArgoCD, Helm, Dapr and GitOps workflows
• Database technologies including MongoDB and PostgreSQL
• DevSecOps, Infrastructure as Code and CI/CD practices
• Large‑scale data platforms, data warehouses or lakehouses (Databricks experience is advantageous)