Key Competencies :

- Data Modelling & Data Architecture

- Dimensional Data Modelling

- Data Governance

- Data Analysis & Profiling

- Enterprise Data Management

- Stakeholder Management

- Problem Solving

- Documentation & Standards

- Communication & Collaboration

Job Description :

Key Responsibilities :

Data Modelling & Design :

- Design, develop, and maintain enterprise-level conceptual, logical, and dimensional data models.

- Create and manage normalized (3NF) data models for operational systems and dimensional models for reporting and analytics.

- Ensure data models align with business requirements, enterprise architecture standards, and data governance policies.

- Define and maintain data modelling standards, methodologies, naming conventions, and best practices.

- Perform data analysis and profiling to identify relationships, dependencies, and data quality issues.

Data Governance & Integration :

- Collaborate with business data governance teams to establish and maintain data definitions, business glossaries, and metadata standards.

- Support enterprise master data management initiatives by defining data entities, relationships, and ownership structures.

- Develop data flow models, CRUD matrices, and process maps to understand data movement across systems.

- Ensure consistency and integrity of enterprise data assets across multiple applications and platforms.

Stakeholder Collaboration :

- Work closely with Data Analysts, Business Analysts, Information Architects, Data Engineers, Solution Architects, and Project Managers.

- Translate complex technical data structures into business-friendly terminology and documentation.

- Participate in project planning, solution design workshops, and architecture reviews.

- Support strategic initiatives involving enterprise data transformation and modernization programs.

Data Quality & Process Improvement :

- Analyze existing data structures and identify opportunities for optimization and standardization.

- Recommend process improvements related to data architecture, modelling, integration, and governance.

- Conduct impact assessments for system changes affecting data structures and integrations.

- Support data quality initiatives through effective data modelling practices.

Documentation & Standards :

- Create and maintain comprehensive data model documentation, data dictionaries, lineage diagrams, and metadata repositories.

- Ensure compliance with enterprise data standards and regulatory requirements.

- Provide knowledge sharing and mentoring to project teams on data modelling best practices.

Required Skills & Qualifications :

Mandatory Skills :

- 12 + years of experience in Data Modelling and Data Architecture.

- Strong experience in developing and maintaining :

1. Conceptual Data Models

2. Logical Data Models

3. Physical Data Models

4. 3NF (Third Normal Form) Data Models

5. Dimensional Data Models (Star Schema & Snowflake Schema)

- Hands-on experience with data modelling tools such as :

1. ER/Studio

2. Erwin Data Modeler

3. PowerDesigner

4. Similar enterprise modelling tools.

- Strong knowledge of :

1. Relational Database Management Systems (RDBMS)

2. SQL Databases

3. NoSQL Databases.

- Experience creating :

1. Entity Relationship Diagrams (ERD)

2. Data Flow Diagrams

3. CRUD Matrices

4. Data Dictionaries

- Understanding of Master Data Management (MDM) concepts.

- Strong exposure to Software Development Lifecycle (SDLC) and IT Project Lifecycle.

- Excellent analytical, problem-solving, and communication skills.

- Ability to communicate technical concepts effectively to business stakeholders.

Domain Expertise :

- Mandatory experience in the Life Sciences / Pharmaceutical domain.

- Understanding of pharmaceutical business processes, regulatory requirements, and enterprise data landscapes will be highly preferred.

Preferred Skills :

- Knowledge of Data Governance frameworks and Metadata Management.

- Exposure to Cloud Data Platforms (Azure, AWS, or GCP).

- Experience with Data Warehousing and Analytics environments.

- Familiarity with ETL/ELT concepts and data integration patterns.

- Understanding of enterprise architecture frameworks. Experience working in global delivery models and stakeholder management.

Educational Qualification :

- Bachelor's Degree or Master's Degree in :

1. Computer Science

2. Information Technology

3. Engineering

4. Data Science

- Or related discipline from a reputed institution.