The Data Modeler is responsible for designing, developing, and maintaining enterprise data models that support business processes, analytics, and application development. This role works closely with business stakeholders, solution architects, data engineers, and development teams to ensure data structures are scalable, efficient, secure, and aligned with organizational standards.
The Data Modeler plays a key role in defining logical and physical data models, ensuring data quality, consistency, governance, and integration across systems.
Key Responsibilities
Data Modeling & Design
- Design and maintain conceptual, logical, and physical data models for enterprise applications and platforms.
- Analyze business requirements and translate them into efficient data structures and database designs.
- Define data relationships, schemas, mappings, and metadata standards.
- Ensure scalability, performance, integrity, and security of data models.
Database & Data Management
- Collaborate with database administrators and developers to optimize database performance and storage strategies.
- Support data migration, integration, and transformation activities across systems.
- Ensure consistency and standardization of enterprise data definitions and naming conventions.
- Participate in database design reviews and data architecture discussions.
Governance & Quality
- Maintain data dictionaries, metadata repositories, and documentation.
- Ensure compliance with data governance, regulatory, and security standards.
- Identify and resolve data quality issues, redundancies, and inconsistencies.
- Support master data management and data lineage initiatives.
Collaboration & Stakeholder Management
- Work closely with business analysts, architects, and engineering teams to align data solutions with business goals.
- Support reporting, analytics, and business intelligence initiatives.
- Provide guidance on best practices for data management and modeling.
Required Skills & Experience
- Strong experience in data modeling and database design.
- Proficiency in SQL and relational databases (Oracle, SQL Server, PostgreSQL, etc.).
- Experience with data modeling tools such as ERwin, ER/Studio, PowerDesigner, or similar.
- Strong understanding of normalization, dimensional modeling, and data warehousing concepts.
- Knowledge of ETL, data integration, and data governance principles.
- Excellent analytical and problem-solving skills.
Preferred Qualifications
- Experience with cloud data platforms (AWS, Azure, GCP).
- Knowledge of big data technologies and distributed data systems.
- Familiarity with Agile methodologies and SDLC processes.
- Experience in banking, finance, insurance, or enterprise domains preferred.