DMK is a production-heavy organization running SAP across manufacturing, logistics, and supply-chain functions while investing in predictive maintenance, production-line integration, and SCADA/MES optimization. Hiring is concentrated in manufacturing (63 roles) and engineering (18), with accelerating velocity — a pattern typical of facilities scaling capacity or modernizing legacy infrastructure. The stack reveals reliance on SAP modules (MM, SD, PM, ERP) paired with industrial control systems (Siemens S7, TIA Portal, Schneider Electric), suggesting ongoing investment in automation and real-time production visibility.
Notable leadership hires: Head of Packing
DMK is Germany's largest dairy cooperative, processing milk into cheese, dairy products, baby food, ice cream, vegan products, and ingredients under brands including MILRAM, Oldenburger, Uniekaas, and Alete. Headquartered in Bremen with approximately 6,800 employees across 20+ locations in Germany, the Netherlands, and select international markets, DMK is a major supplier to German food retail and generated €5.1 billion in revenue. The operational focus spans multiple product categories and distribution channels, with active projects centered on production-line integration, maintenance process improvement, and predictive maintenance deployment across manufacturing facilities.
SAP (ERP, MM, SD, PM modules), Siemens S7 / TIA Portal industrial controllers, SCADA / MES systems, SQL Server, and specialized tools like LIMS, NielsenIQ, and SAP BusinessObjects BI for supply chain, quality, and business intelligence.
Integration of new production lines, predictive maintenance rollout, continuous improvement of maintenance planning and processes, SCADA/MES optimization, test method refinement, and enterprise system integration — aligned with reducing downtime and ensuring production quality across its dairy manufacturing network.
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DMK Deutsches Milchkontor GmbH'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.