Data Management & Infrastructure Manager
At a glance
Manager-level Data Architecture & Governance role at Novartis. Milano · full-time.
Pay not stated Data Architecture & Governance salary
dataroles summary, based on the employer's posting.
What you'll do
- Run the country data foundation so teams can rely on one view of critical information from internal and external sources
- Set rules for data intake, transformation, aggregation and master data, then coordinate flows across key platforms
- Improve data quality checks, investigate issues and maintain privacy, access and promotional-data safeguards
- Keep reporting data ready for dashboards, analytics and AI use cases; investigate anomalies and their underlying causes
- Work with stakeholders and providers on data needs, quality expectations and operational measures
What you bring
- A university degree in a technical or related field, such as business, life sciences, mathematics or computer science
- At least five years in data architecture, master data management or enterprise data strategy
- Experience owning data products, including requirements, user stories, acceptance criteria and delivery across teams
- Strong knowledge of pharmaceutical data, regulatory standards and the boundary between promotional and non-promotional work
- Expertise in SQL and data management, plus English proficiency
Who this fits
This manager role suits someone who can connect data architecture and governance with reporting, analytics and product delivery. It is based in Milano, Italy. English is required; Italian is preferred.
From the employer
Salary Range:
44.100,00 € - 81.900,00 €
Job Description Summary
The Data Management & Infrastructure Manager will be the Data, Analytics and Platforms team's country representative (within the Execution Excellence unit) for the data foundation. 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 Description
Key responsibilities
DATA 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 reports or dashboards
- Enable new analytics and AI/GenAI use cases by ensuring data readiness for country‑priority pilots and scaled solutions
CROSS-FUNCTIONAL COLLABORATION
- Partner with internal and external stakeholders to understand and meet data needs across the product lifecycle.
- Support vendor and budget management by defining requirements, quality standards, and performance feedback for external data and technology providers, while tracking key data quality, governance, and operational KPIs.
Essential requirements
- University degree in Business, Life Sciences, Mathematics, Statistics, Computer Science, Engineering, Analytics, or a related technical field.
- 5+ years of experience in data architecture, master data management, or enterprise data strategy.
- Experience as a Data Product Owner, managing business requirements, features, user stories, acceptance criteria, and cross-functional product delivery.
- Strong knowledge of pharma data domains including commercial, patient services, market access, digital, medical, and omnichannel data ecosystems.
- Understanding of the pharmaceutical regulatory environment, industry standards, and the separation of promotional and non-promotional activities and data.
- Proven ability to drive data strategy, enable new datasets, and deliver automation, optimization, and change management initiatives.
- Expertise in SQL and data management; knowledge of Python or R and data engineering concepts; knowledge of data governance/quality tools and data platforms.
- Strong analytical, problem-solving, communication, consulting, and stakeholder-influencing skills
- English required, Italian preferred, with a strong ethical and leadership mindset.
Why Novartis? Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us! Learn more here: https://www.novartis.com/about/strategy/people-and-culture
Benefits and rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards
Commitment to Diversity and Inclusion:
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.
People and culture
Skills Desired
Analytical Thinking, Brand Awareness, Business Analytics, Cross-Functional Collaboration, Digital Marketing, Media Campaigns, Project Management, Project Planning, Sales, Stakeholder Engagement, Stakeholder Management, Waterfall Model