V-ZUG manufactures long-lasting home appliances from its Zug headquarters, with a tech stack anchored in SAP (Commerce, S/4HANA, SD, MM) and embedded systems (STM32, ARM Cortex-M, C/C++). The hiring mix—engineering-heavy with quality and manufacturing roles—reflects active development of mobile apps (V-ZUG Home, Diagnose) and an IoT platform alongside process digitalization. Pain points center on traceability gaps between requirements and tests, production stability, and recruiting skilled labor—typical scaling friction for a 110-year-old manufacturer moving into software-enabled products.
Notable leadership hires: Manufacturing Team Lead
V-ZUG is a publicly traded Swiss manufacturer founded in 1913, specializing in kitchen and home appliances with a focus on sustainability and carbon-neutral production. The company operates across Switzerland with ~1,000–5,000 employees. Beyond traditional appliance manufacturing, V-ZUG is building digital product surfaces: a consumer app (V-ZUG Home), a diagnostics app, and an IoT platform to extend product connectivity. Manufacturing processes are supported by SAP ERP, quality frameworks (FMEA, MSA, SPC, 8D), and embedded firmware on microcontroller platforms. Active hiring targets engineering, support, and production roles, with accelerating velocity.
V-ZUG runs SAP (Commerce, S/4HANA, SD, MM, Cloud Platform), embedded systems (STM32, ARM Cortex-M, C/C++, CMake), web/mobile testing (Playwright, Cypress, Selenium, BrowserStack, JavaScript, TypeScript), and quality/manufacturing tools (FMEA, MSA, SPC, Polarion). Analytics via Google Analytics 4 and Adobe Analytics.
V-ZUG is developing the V-ZUG Home consumer app, a Diagnose app for product support, and an IoT platform. Active projects also include requirements management expansion, manufacturing process audits, and continuous improvement via field complaint analysis.
V-ZUG'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.