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Intersnack in Düsseldorf is seeking an AI Engineer for Analytics & End-User Insights to bridge enterprise data architecture with business users. You will design data pipelines, implement AI-driven reporting, and define technical KPIs with explainability and observability across AI outputs.
You will lead semantic layer development, enable natural-language querying, and support adoption of AI-enabled workflows while ensuring security-by-design and GDPR compliance across IT, data, and business
We Want You to Grow With Us Intersnack is building a next-generation AI and data foundation and this role is at the heart of making that foundation meaningful for the people who rely on it every day. As our AI Engineer for Analytics & End-User Insights, you will bridge the gap between enterprise data architecture and the business users who depend on trustworthy, actionable intelligence to make decisions. You will report into the AI Programme and collaborate across procurement, manufacturing, and sales to deliver AI-powered reporting that business teams can understand, trust, and act on.
What We Can Offer You will join a collaborative, internationally minded team building something genuinely new: a modern, AI-grounded analytics capability that complements existing reporting and serves real business decisions. This role offers significant autonomy to shape how AI is introduced into the daily workflows of colleagues across multiple functions and countries. The impact of your work will be visible and measurable, from the moment a business user receives an AI-generated insight they trust, to the gradual reduction of manual reporting steps that once dominated their week.
Dusseldorf serves as your home base, with flexibility for remote working, and the broader Intersnack network gives you exposure to a truly international operating environment.
You will operate at the intersection of data engineering, AI, and business enablement: designing the data supply chain and semantic infrastructure that makes AI-driven analytics possible, while ensuring that the people who consume those analytics are equipped to use them with confidence. Your focus spans architecture and adoption in equal measure, working closely with business stakeholders to define what good looks like and then building the pipelines and models to get there.
Mots-clés : Information Management.