Data & Analytics Senior Specialist

01 ago - Modena
Experteer Italy

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 Data Ops 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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