Data & Analytics Senior Specialist
CNH ·
About Us 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.
About Us 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 benefit 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 ability to relate architectural decisions to business value.
Mastery of data modeling and data architecture patterns (dimensional, data vault, medallion/Lakehouse). Solution evaluation and comparison; reference‑architecture design. Working knowledge of data governance and data quality principles (the role applies them and collaborates with the Data Governance function, but does not own governance).
Technical Databricks Lakehouse (core requirement): Apache Spark, Delta Lake, Unity Catalog, Workflows/Jobs, Delta Live Tables, MLflow. Cloud: Azure (Azure Data Lake Storage; Databricks on Azure); AWS knowledge a plus. Data integration awareness of AI/GenAI data enablement (vector search, semantic layers, feature stores). Methodology Agile / SAFe, DevOps