Clinical Data Modeler

Astellas-5c3299a9; Bengaluru; Hybrid; INR 900,000 - 1,400,000; Full time

Job summary

Astellas is seeking an experienced Clinical Data Modeler to design, build, deploy, and maintain scalable, governed data pipelines and reusable data products on the Databricks platform. You will collaborate with Clinical Operations, Data Management, and AI stakeholders to transform raw data into trusted assets across the five-layer architecture.

The role requires strong data modeling expertise in pharmaceutical Development data, experience with clinical and operational data, and the ability to

Qualifications

• 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 clinical and operational 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 clinical and operational 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.

Responsibilities

• Design and maintain conceptual, canonical, logical, semantic, and physical data models for pharmaceutical Development data products.
• Translate clinical, operational, safety, regulatory, and business requirements into reusable enterprise information models.
• Define core Development entities, attributes, identifiers, relationships, hierarchies, events, lifecycle states, temporal relationships, and business rules.
• Establish canonical representations across studies, countries, sites, vendors, clinical systems, and Development functions.
• Model longitudinal relationships to understand study, site, investigator, subject, visit, milestone, safety, and trial execution over time.
• Ensure models support operational reporting, advanced analytics, machine learning, generative AI, and application integration.
• Apply relational, dimensional, graph, document, event-based, and other modeling techniques based on business 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.

Skills

Data modeling

Information architecture

Analytics engineering

Enterprise data management

Clinical data

Relational modeling

Stakeholder management

Facilitation/communication

Education

Bachelor or Master in information systems/CS/Life Sciences

Tools

Databricks

Unity Catalog

ER/Studio

erwin

PowerDesigner

Hackolade

Job description

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 dynamic 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 Clinical 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 Clinical Operations, Data Management, Statisticians, Data Product Owners, Domain Data Architects, Domain Data Modelers, 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' five-layer architecture: Bronze, Silver, Silver+, Gold, and Platinum.

The successful candidate will combine strong data modeling expertise with knowledge of pharmaceutical Development data and an ability to facilitate alignment among clinical, operational, governance, architecture, engineering, and AI stakeholders.

Responsibilities and Accountabilities:

• Design and maintain conceptual, canonical, logical, semantic, and physical data models for pharmaceutical Development data products.
• Translate clinical, operational, safety, regulatory, and business requirements into reusable enterprise information models.
• Define core Development entities, attributes, identifiers, relationships, hierarchies, events, lifecycle states, temporal relationships, and business rules.
• Establish canonical representations across studies, countries, sites, vendors, clinical systems, and Development functions.
• Model longitudinal relationships require to understand study, site, investigator, subject, visit, milestone, safety, and trial execution over time.
• Ensure models support operational reporting, advanced analytics, machine learning, generative AI, and application integration.
• Apply relational, dimensional, graph, document, event-based, and other modeling techniques based on business 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.

Requirements

Required Qualifications:

• 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 clinical and operational 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 clinical and operational 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.

Preferred Qualifications:

• Experience supporting pharmaceutical, biotechnology, or life sciences Development.
• Knowledge of one or more Development areas such as Clinical Development, Clinical Operations, Clinical Data Management, Safety, Regulatory, or CMC.
• 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 semantic modeling, controlled vocabularies, taxonomies, clinical terminologies, or knowledge graphs.
• Familiarity with Genie, natural-language analytics, semantic layers, or AI agent enablement.
• Understanding of relevant clinical and regulatory data standards.
• 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.

Our Organizational Values and Behaviors

Values: Innovation, IntegrityandImpactsit at the heart of what we do.

Behaviors: We come together as‘One Astellas’,working withcourageand a sense ofurgency. We are outcome focusedand consistently takeaccountabilityfor our personalcontribution.

Our organization is committed to diversity, equal opportunity, and affirmative action. We are an equal opportunity employer. All applicants will be considered without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity, or any other protected characteristic.

EEO is the Law