Position Title: Asc. Dir. Dev. IT Data, Analytics, DS&AI

Location – Hyd-India #LI Hybrid

About the Role

The Development Data Enablement team delivers high-quality data solutions and models across Drug Development functions, ensuring solutions adhere to enterprise information architecture standards and support the organization's data strategy. With a strong focus on conceptual, logical, and physical data modeling, metadata management, and integration into enterprise data sources and platforms, the team plays a key role in enabling trusted, accessible, and compliant data for analytics, operations, and regulatory reporting.

As an Associate Director Solution Delivery Data Modeler, you will work on the design, delivery, and governance of enterprise and system solution data models for domain-specific projects, ensuring they comply with enterprise modeling guidelines, industry best practices, and governance policies.  This is a hands-on delivery role with accountability for both technical quality and governance adherence. You will collaborate closely with business analysts, solution architects, data engineers, enterprise data owners, and domain teams to translate requirements into high-quality, reusable data model assets.

This role reports to the Data Delivery Lead within the Data, Analytics, and DS&AI function for the Development domain.

Your responsibilities include but are not limited to

• Develop and maintain conceptual, logical, and physical data models using Novartis data modeling guidelines; ensure data models are in conformance with relevant industry standards and enterprise best practices.
• Assist to establish, maintain, and evolve information architecture best practices, guidelines, principles, and standards in alignment with the Novartis Data Strategy team’s vision.
• Drive data modeling initiatives and assist in the architecture, design, and development of the overall data architecture.
• Capture, maintain, and govern metadata and business glossary entries in the enterprise data catalog solution.
• Review proposed data models contained in packaged or commercially available applications before purchase to ensure compliance with enterprise modeling and governance standards.
• Guide, educate, and mentor members of the data community on the data strategy directives, principles, and standards.
• Take accountability to ensure adherence to security, compliance, and privacy policies and procedures within the Enterprise Information Architecture scope.
• Collaborate with business partners, IT teams, architecture teams, and vendor partners to design and prepare data models that meet functional and technical requirements.
• Define and enforce compliance to data modeling best practices, including leading and participating in data design reviews during solution delivery.
• Work closely with data engineering teams to implement approved data models in target systems, ensuring correct integration and deployment.
• Partner with business and technology teams to capture and translate data requirements into models for EDW, Data lake and Lakehouse architectures 
• Monitor and report on compliance of models with enterprise data governance frameworks and quality standards.
• Support the ongoing evolution of data models in response to changes in business processes, data sources, and technology platforms.
• Collaborate with solution and domain architects to ensure data models integrate seamlessly into the broader architecture and data flows.
• Provide education, guidance, and mentoring to project teams on data modeling principles, enterprise standards, and best practices.

What you’ll bring to the role:

• Quality, maintainability, and scalability of delivered data models. Compliance of models with enterprise data strategy, modeling guidelines, and data governance standards.
• Accuracy and completeness of metadata and business glossary entries. Timeliness and usability of data models delivered to meet project schedules. Reduced rework and improved reuse of data models across the organization.

• Ability to design and apply ontology models to define domain concepts, relationships, and taxonomies for consistent data interpretation and integration is preferred
• Proficient in multiple database paradigms (relational, dimensional, graph, file/unstructured). Experience validating and modeling data schemas for both custom and packaged applications. Experience with metadata and data cataloging tools.
• Strong data analysis skills for understanding, profiling, and mapping sources to target models. Background in life sciences or pharmaceutical industry is strongly preferred. Experience working in diverse, cross-functional, and multicultural project teams.

• Data Modeling Expertise (Conceptual, Logical, Physical), Metadata Management and Business Glossary Development. Data Governance and Standards Adherence
• Cross-functional Collaboration and Communication, Problem Solving and Analytical Thinking. Stakeholder Engagement and Business Acumen, Continuous Learning and Technical Curiosity. Technical / Functional Skills & Knowledge
• Understanding data security, privacy, and compliance requirements in pharma/life sciences.

Desirable Requirements:

• Bachelor’s degree in Computer Science, Information Systems, or related technical discipline; advanced degree or relevant certifications a plus.
• 12+ years of experience as a Data Modeler / Data Architect in large-scale, multi-national enterprise environments. Hands-on expertise in conceptual, logical, and physical data modeling for EDW, data lake, and operational reporting systems.
• Strong knowledge of semantic data modeling approaches. Strong experience applying enterprise data modeling standards and governance best practices in alignment with frameworks such as DCAM and DAMA-DMBOK.
• Familiarity with life sciences/pharmaceutical data standards and regulations such as IDMP, SEND, CDISC, and other relevant regulatory frameworks.
• Proficiency with ER modeling tools (e.g., ER/Studio, ERwin, PowerDesigner). Familiarity with enterprise data cataloging tools (e.g., Collibra). Knowledge of SQL and data query tools for validation and profiling.
• Experience in integrating models with modern cloud-based and on-premises platforms. Knowledge of ETL/ELT processes, data warehousing concepts, and big data environments.

Commitment to Diversity & Inclusion:

Novartis embraces diversity, equal opportunity, and inclusion. We are committed to building diverse teams, representative of the patients and communities we serve, and we strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.