Associate Director, Data Modelling Lead
Novartis
Summary
As Associate Director, Data Modeling, you will play a critical role in designing and governing enterprise data assets that support analytics, reporting, and AI-ready datasets across Novartis. You'll partner with business and technology leaders to create scalable, reusable data models that power innovation and informed decision-making.
Job description
Key Responsibilities
- Design and govern conceptual, logical, and physical enterprise data models.
- Translate business requirements into scalable, implementation-ready data structures.
- Model critical enterprise domains, including customer, product, payer, and territory data.
- Partner with business and technical teams to define entities, relationships, and business rules.
- Establish and maintain enterprise data modeling standards and design patterns.
- Review and approve data models for alignment with Common Data Model standards.
- Ensure data models are accurately represented within metadata and lineage platforms.
- Support certified data products with governed, reusable, AI-ready data structures.
- Identify and resolve data model gaps, duplication, and cross-domain inconsistencies.
- Provide data modeling expertise, documentation, and design guidance to stakeholders and engineering teams.
Essential Requirements
- Bachelor's degree in Data Management, Information Systems, Computer Science, Engineering, Analytics, Business, or related field.
- 5+ years of experience in data modeling, data architecture, data engineering, or enterprise data management.
- Experience building conceptual, logical, and physical data models for enterprise data platforms, data products, master data, or CDM programs.
- Experience working with business and technical teams to translate requirements into implementable data structures.
- Experience with data product, data warehouse, lakehouse, or analytics platform environments.
Desirable Requirements
- Advanced degree or relevant data architecture, data modeling, cloud, or data management certification preferred.
Requirements
- Bachelor's degree in Data Management, Information Systems, Computer Science, Engineering, Analytics, Business, or related field.
- 5+ years of experience in data modeling, data architecture, data engineering, or enterprise data management.
- Experience building conceptual, logical, and physical data models for enterprise data platforms, data products, master data, or CDM programs.
- Experience working with business and technical teams to translate requirements into implementable data structures.
- Experience with data product, data warehouse, lakehouse, or analytics platform environments.
- Advanced degree or relevant data architecture, data modeling, cloud, or data management certification preferred.
Benefits
- Health insurance
- Life insurance
- Disability benefits
- 401(k) with company match
- Vacation
- Personal days
- Holidays
- Performance-based cash incentive
- Annual equity awards
Company overview
Novartis is a global pharmaceutical company headquartered in Basel, Switzerland, dedicated to reimagining medicine to improve and extend people's lives. As an innovative medicines company, Novartis focuses on developing high-value treatments that address society's greatest disease burdens through technology leadership in research and development. The company operates across five core therapeutic areas: cardiovascular, renal and metabolic diseases; immunology; neuroscience; oncology; and hematology. With a workforce of approximately 75,883 employees worldwide, Novartis reaches nearly 300 million patients across 118 countries. The company leverages advanced technology platforms including targeted protein degradation, cell therapy, gene therapy, radioligand therapy, and xRNA to develop breakthrough treatments. Novartis maintains a strong portfolio of oncology drugs and generics while continuously expanding its pipeline through strategic acquisitions and internal research. The company's commitment extends beyond drug development to ensuring global access to medical innovations through novel access approaches and patient assistance programs.