Burberry

Burberry

In an exceptional project with Burberry, a globally recognised luxury fashion brand, we took on the challenge of working on high-load microservices for e-commerce. Leveraging big data and machine learning, our team successfully created robust, scalable solutions that significantly improved Burberry's digital operations.

Under our leadership, the project backlog was efficiently cleared across three streams. A key achievement was the development of our junior software engineers who, with expert guidance, were able to support and extend over 20 APIs. This demonstrated our commitment not only to technological advancement, but also to the growth and development of our team.

Our role encompassed a wide range of responsibilities, including maintaining and extending dozens of microservices related to personalisation and personal data services. We pioneered the creation of over 10 new microservices and migrated existing ones using Node.js, AWS from Apigee. Further enhancements were made to our main API template, integrating extensive CI/CD functionality, reducing the time to market from weeks to days or even hours.

Our team also developed and extended npm packages, strengthening our Node.js skills. At the same time, we focused on internal team development, interviewing potential candidates and actively encouraging team growth. Part of our success in this area was due to our focus on maintainability and readability of the codebase, making it much easier for newcomers of all skill levels to join the project.

To streamline and automate various aspects of the development process, we deployed tools and strategies such as test generation from Swagger, semantic versioning and automated releasing.

We also made significant contributions to internal projects such as the development of an end-to-end testing platform, a development portal and a dynamic dashboard, demonstrating our versatility and commitment to continuous improvement.