Astellas is a global life sciences company committed to turning innovative science into VALUE for patients. We provide transformative therapies in disease areas that include oncology, ophthalmology, urology, immunology and women's health. Through our research and development programs, we are pioneering new healthcare solutions for diseases with high unmet medical need. Learn more at Astellas.com

Are you driven to make a real difference in the lives of patients?

We're seeking passionate individuals who thrive in energetic environments, embrace new ideas, and aren't afraid to take intelligent risks. People who act with unwavering integrity and are deeply committed to making a tangible impact.

Purpose and Scope:

- We are seeking an experienced Research Data Modeler to design, build, deploy, and maintain reliable, scalable, and governed research data pipelines and reusable data products supporting Research & Discovery, translational science, analytics, reporting, AI, and scientific decision-making.
- Working with Research scientists, Data Product Owners, Domain Data Architects, Data Governance Specialists, Data Scientists, and Platform Engineers, this role transforms raw scientific and laboratory data into trusted assets on the Databricks Data Intelligence Platform across Astellas medallion architecture.
- The successful candidate will combine strong data modeling expertise with knowledge of pharmaceutical Research and Discovery data and an ability to facilitate alignment among scientific, business, governance, architecture, engineering, and AI stakeholders.

Responsibilities and Accountabilities:

- Design and maintain conceptual, canonical, logical, semantic, and physical data models for Research and Discovery data products.
- Translate scientific, experimental, and business requirements into reusable enterprise information models.
- Define core Research entities, attributes, identifiers,



relationships, hierarchies, experimental context, events, and scientific business rules.
- Establish canonical representations across laboratories, research sites, source systems, external providers, and data products.
- Model structured, semi-structured, unstructured, and multimodal scientific data while preserving provenance and experimental context.
- Ensure models support scientific analysis, advanced analytics, machine learning, generative AI, knowledge graphs, and application integration.
- Apply relational, dimensional, graph, document, event-based, and other modeling techniques based on scientific and technical requirements.
- Maintain clear separation between source-aligned models, canonical domain models, governed data products, and consumption-specific assets.
- Work with the Domain Data Architect and Data Product Owners to translate the approved domain data product roadmap into actionable modeling deliverables.
- Define the information models needed to support planned data products, use cases, releases, and AI capabilities.
- Identify common entities and reusable modeling components that can serve multiple data products.
- Sequence modeling work based on product priorities, source dependencies, governance readiness, and engineering needs.
- Provide modeling estimates, assumptions, dependencies, risks, and decisions required for product delivery.
- Participate in backlog refinement and help define modeling stories, acceptance criteria, and definitions of done.
- Ensure delivered models remain aligned with the target-state domain architecture and product portfolio.
- Develop canonical models that harmonize semantically equivalent data across multiple source systems.
- Define authoritative entity structures, relationships, cardinality, keys, reference data, and lifecycle states.
- Establish standards for enterprise identifiers and cross-system identity resolution.

📌 Research Data Modeler (India)
🏢 Astellas
📍 India