Data Management & Infrastructure Manager

Novartis

Lombardia

On-site

EUR 44,000 - 82,000

Full time

40 hours ago
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Job summary

Novartis in Italy seeks a Data Management & Infrastructure Manager to own the country data foundation across Commercial, Value & Access and Medical. You will design, operate, and improve a single, trusted view of business-critical data in line with international standards.

You will partner with local stakeholders to ensure data, platforms and reporting solutions are fit-for-purpose and adopted across the organization, while complying with governance and AI ethics.

Qualifications

  • University degree in a technical or related field.
  • 5+ years in data architecture, MDM or data strategy.
  • Experience as a Data Product Owner and cross-functional delivery.
  • Knowledge of pharma data domains and regulatory environment.

Responsibilities

  • Own and optimize the country data foundation across sources.
  • Define data ingestion, transformation, and master data rules.
  • Coordinate data integration and ensure analytics readiness.
  • Ensure alignment with data governance, privacy and ethics.
  • Maintain data layer for reporting, dashboards and AI use cases.

Skills

Data architecture
Master data management
Stakeholder management
SQL
Python or R
Data governance
Problem solving
Communication
Leadership

Education

University degree

Job description

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 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.

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
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