Research Data Modeler

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

• 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.

• →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.

• Bachelor’s or master’s degree in Information Systems, Computer Science, Data Management, Bioinformatics, Life Sciences, Engineering, or a related discipline.
• Five or more years of experience in data modeling, information architecture, data architecture, analytics engineering, or enterprise data management.
• Experience working with research data, research data platforms, and pipelines
• Demonstrated experience developing conceptual, logical, canonical, dimensional, semantic, and physical data models.
• Strong knowledge of relational modeling, normalization, dimensional modeling, entity-relationship modeling, and metadata management.
• Experience translating complex scientific requirements into reusable information models.
• Experience defining entities, relationships, identifiers, hierarchies, reference data, and business rules.
• Experience collaborating with architects, Product Owners, engineers, Governance Specialists, and business subject matter experts.
• Strong facilitation, communication, documentation, and stakeholder-management skills.

• Experience supporting pharmaceutical, biotechnology, or life sciences Research and Discovery.
• Knowledge of one or more Research areas such as discovery biology, target biology, medicinal chemistry, compound and assay data, translational science, or preclinical research.
• Experience with Databricks, Unity Catalog, or comparable cloud data and metadata platforms.
• Experience with data modeling tools such as ER/Studio, erwin, SAP PowerDesigner, Hackolade, or comparable solutions.
• Experience with scientific ontologies, knowledge graphs, controlled vocabularies, taxonomies, or semantic modeling.
• Familiarity with Genie, natural-language analytics, semantic layers, or AI agent enablement.
• Familiarity with FAIR data principles and scientific data provenance.

• This position is based in Bengaluru GCC and will require 2 days/week on-site work.
• (OR) At Astellas we recognize the importance of work/life balance, and we are proud to offer a hybrid working solution allowing time to connect with colleagues at the office with the flexibility to also work from home. We believe this will optimize the most productive work environment for all employees to succeed and deliver. Hybrid work from certain locations may be permitted in accordance with Astellas’ Responsible Flexibility Guidelines. Global collaboration and limited travel may be required.

Values: Innovation, Integrity and Impact sit at the heart of what we do. 

Behaviors: We come together as ‘One Astellas’, working with courage and a sense of urgency. We are outcome focused and consistently take accountability for our personal contribution. 

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