Data Management
Pubblicato il 20-10-2026 - Novartis in Padova
Salary Range: 44.100,00 € - 81.900,00 € Job Description Summary The Data Management & Infrastructure Manager is the country referent for the Data, Analytics and Platforms data foundation within the Execution Excellence unit. The role designs, operates, and continuously improves a single, trusted view of business-critical data across Commercial, Value & Access and Medical, in line with international data strategy and governance frameworks. The role partners closely with local stakeholders to ensure that data, platforms and reporting solutions are fit-for-purpose, aligned with international standards, and sustainably adopted across the organization. Job DescriptionKey responsibilitiesDATA MANAGEMENT & INFRASTRUCTURE * Own and optimize the country Data, Analytics and Platforms data foundation, delivering a single, trusted view of business-critical data across internal and external sources. * Define and govern business rules for data ingestion, transformation, aggregation, and master data management in line with enterprise standards.
* Coordinate data integration and flows across key platforms, ensuring timely, accurate, and analytics-ready data. * Ensure alignment with global data governance, architecture, privacy, compliance, and AI ethics requirements through collaboration with internal and external stakeholders. DATA QUALITY, GOVERNANCE & COMPLIANCE ENABLEMENT * Implement, monitor, and continuously improve data quality controls, resolving data issues and strengthening trust in data. * Support adherence to data privacy and promotional/non‑promotional standards by ensuring appropriate data access models * Contribute to data policies and documentation, including data dictionaries, lineage descriptions and usage guidelines REPORTING AND ANALYTICS ENABLEMENT * Maintain and enhance the data layer supporting reporting, dashboards, analytics, and AI/GenAI use cases, ensuring consistency and data readiness. * Perform data validation and root‑cause analysis for anomalies in r