Data Modeler & Data Architect

Job Description : 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

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 :

• Conceptual Data Models

• Logical Data Models

• Physical Data Models

• 3NF (Third Normal Form) Data Models

• Dimensional Data Models (Star Schema & Snowflake Schema)

Hands-on experience with data modelling tools such as :

• ER/Studio

• Erwin Data Modeler

• Power Designer

• Similar enterprise modelling tools.

Strong knowledge of :

• Relational Database Management Systems (RDBMS)

• SQL Databases

• NoSQL Databases.

Experience creating :

• Entity Relationship Diagrams (ERD)

• Data Flow Diagrams

• CRUD Matrices

• 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 :

• Computer Science

• Information Technology

• Engineering

• Data Science Or related discipline from a reputed institution.