Irish retail chain modernizing legacy systems with cloud and data platforms
Dunnes Stores operates a legacy retail technology stack built on AS/400, Oracle EBS, and Forms — but is actively modernizing toward Azure, .NET, and cloud-native data infrastructure (Azure Synapse, Data Factory, Fabric). The hiring acceleration skews heavily toward senior and lead roles in data and engineering, signaling investment in building internal technical capability rather than outsourcing the transformation. Current pain points (shadow systems, compliance gaps, supply-chain digitization) and projects (Dublin engineering hub, cybersecurity strategy, ecommerce roadmap) reveal a multi-front modernization effort.
Notable leadership hires: Head of Engineering
Dunnes Stores is a privately held Irish retailer founded in 1944, operating over 10,000 employees across fashion, homewares, and food retail. The company runs a complex, multi-channel operation spanning stores, supply chain, and digital channels. Historically built on enterprise systems (Oracle suite, AS/400), the business is now undertaking a platform modernization toward cloud infrastructure and strengthening internal engineering and data teams, particularly through a new Dublin-based engineering hub.
Core systems: AS/400, Oracle EBS, Oracle Retail, and Oracle HCM Cloud for enterprise operations. Cloud: Azure (Synapse, Data Factory, Fabric). Development: C#, .NET. Data and analytics: Power BI, Microsoft Fabric, PL/SQL. Networking: Cisco.
Cloud modernization on Azure; digital product roadmap for ecommerce, mobile, and loyalty; compliance automation; cybersecurity strategy; third-party risk assessment; and supply-chain digitization and optimization.
Dunnes Stores'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.