Data & Analytics Senior Specialist
Pubblicato il 03-09-2026 - CNH Industrial Group in Modena
Category for Job Posting: Digital and Information Technology
Innovation. Sustainability. Productivity. This is how we are Breaking New Ground in our mission to sustainably advance the noble work of farmers and builders everywhere. With a growing global population and increased demands on resources, our products are instrumental to feeding and sheltering the world.
From developing products that run on alternative power to productivity-enhancing precision tech, we are delivering solutions that vantaggi people – and they are possible thanks to people like you. If the opportunity to build your skills as part of a collaborative, global team excites you, you’re in the right place.
Grow a Career. Build a Future
Be part of this company at the forefront of agriculture and construction, that passionately innovates to drive customer efficiency and success. And we know innovation can’t happen without collaboration. So, everything we do at CNH Industrial is about reaching new heights as one team, always delivering for the good of our customers.
Job Purpose
The main responsibility of this role is to define and govern how data is structured, integrated, stored, and made consumable as reusable data products across CNH on a Databricks-centric Lakehouse platform. The role is responsible for establishing the target-state data architecture, modeling standards, and technology patterns that enable the ingestion, transformation, storage, and enrichment of data. This ensures that CNH’s data foundation is scalable, performant, trusted, and AI-ready, while remaining aligned with Enterprise Architecture, Security, and the broader Data & AI strategy.
Key Responsibilities
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- Define the target-state data architecture and roadmap (conceptual, logical and physical data models) for the enterprise data landscape, maintaining current and target state blueprints.
- Set standards, reference architectures and design guidelines for data ingestion, modeling, storage and consumption on the Databrick