Data & Analytics Senior Specialist

In this role, you will define and govern CNH's data structures, from target-state architecture to reusable data products on a Databricks Lakehouse. You'll establish modeling standards and patterns to enable ingestion, transformation, and enrichment of data at scale, aligned with Enterprise Architecture and Data & AI strategy. You will champion data governance, security, and compliance by design while enabling AI-ready analytics across BI, ML, and GenAI use cases. This position offers impact across programs through technical leadership and collaboration with business and IT stakeholders. opportunities for continuous development competitive compensation Define target-state data architecture and roadmaps (conceptual, logical, physical) for the enterprise data landscape Set standards and reference architectures for data ingestion, modeling, storage, and consumption on the Databricks Lakehouse Architect scalable data pipelines (batch and streaming) and promote a data products operating model with DataOps practices Design AI-/analytics-ready data structures for BI, analytics, ML, and GenAI (vector/semantic layers, RAG-ready data) on Databricks Apply data governance and data quality principles in collaboration with Data Governance for cataloging, lineage, and access management (Unity Catalog) Ensure security, privacy and GDPR/compliance by design Partner with business and IT to translate needs into architectural decisions and maximize data value Provide technical leadership and architectural assurance across programs and external partners 7+ years in data architecture, data engineering, or data modeling Bachelor's degree in related field Strong business-domain understanding and ability to link architecture to business value Mastery of data modeling and architecture patterns (dimensional, data vault, medallion/lakehouse) Experience with reference architectures and evaluation of solutions Knowledge of data governance and data quality principles (collaboration with governance function) Knowledge of data governance and data quality principles (collaboration with governance function) Technical: Databricks Lakehouse stack (Spark, Delta Lake, Unity Catalog, Workflows/Jobs, Delta Live Tables, MLflow); Azure Data Lake Storage; ETL/ELT; Structured Streaming; Kafka/Event Hubs; Python/Spark; AI/GenAI data enablement

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