N+P Informationssysteme GmbH delivers process digitalization for industrial and construction sectors, with engineering-focused hiring (7 of 17 active roles) centered on finance software implementation, ERP development, and warehouse system integration. The tech stack—Azure, SQL Server, Kubernetes, Revit, Autodesk BIM 360—reflects a dual specialization in cloud infrastructure and domain-specific CAD/PLM tooling, while active projects show concentration on legacy-to-hybrid migration and finance workflow automation.
Notable leadership hires: Lead Management Telesales
N+P is a 30-year-old German systems integrator based in Meerane, Sachsen, serving mid-market manufacturing and construction companies. The company combines custom software development (Java, C#, ASP.NET Core) with specialized domain expertise in CAD, CAM, PLM/PDM systems, and Autodesk products. Service lines include system integration, infrastructure planning, training delivery, and process optimization across finance, ERP, and warehouse operations. The hiring momentum (7 roles posted in the last 30 days, primarily engineering and support) indicates scaling of delivery capacity.
Core: Azure, SQL Server, Kubernetes, Terraform. Desktop/Collaboration: Hyper-V, VMware vSphere, Citrix, Exchange Online. Design/Engineering: Revit, Autodesk BIM 360, Autodesk Construction Cloud. Languages: JavaScript, PowerShell, Java, C#, ASP.NET Core, TypeScript.
Active projects: finance software implementation and integration; ERP and warehouse system development; IT system automation; legacy-to-hybrid infrastructure migration; manufacturing and construction process digitalization; customer training delivery.
N+P Informationssysteme 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.