UK food, clothing and home retailer with a growing omnichannel tech platform
Marks and Spencer pairs a large store network with an in-house engineering estate built on Java, Spring Boot and Micronaut running on Azure and Kubernetes, with Databricks and Spark for data. Its SAP S/4HANA adoption and work on Azure AI Foundry and MCP point to ERP modernisation alongside early AI tooling. Hiring is accelerating and skews toward store operations and sales, consistent with a store-reshaping and new-opening push.
Notable leadership hires: Shift Lead, Agronomist Resilience Lead
Marks and Spencer is a public retailer headquartered in London, founded in 1884, with a workforce of over 10,000 employees. It sells quality food, clothing and home products to consumers through stores and digital channels. The company operates across the United Kingdom and hires in Ireland, Canada, Malaysia and Singapore. Its teams span store operations, sales, food, product, finance, data and engineering, supporting both physical retail and online ordering.
M&S uses Java, Spring Boot, Micronaut, Kotlin and TypeScript with React, Next.js and Angular, running on Azure, Kubernetes and Docker, with Databricks, Spark, Power BI, MongoDB, Redis and SQL Server for data.
Yes, SAP S/4HANA is flagged as an emerging technology at M&S, alongside ongoing modernisation of its Azure microservices and integration estate.
M&S hires in the United Kingdom, Ireland, Canada, Malaysia and Singapore, with most activity in store operations and sales roles.
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Marks and Spencer's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.