Data Modeler

A Data Modeler designs, builds, and maintains the blueprints (data models) that define how an organization’s data is structured, stored, and integrated. They bridge the gap between complex business requirements and the technical database systems.

Core Responsibilities

• Design Data Models: Create conceptual, logical, and physical data models to support business applications and enterprise data warehouses.
• Define Data Architecture: Establish naming conventions, data definitions, and metadata standards to ensure consistency across systems.
• Collaborate with Teams: Partner with Data Engineers, Business Analysts, and Database Administrators (DBAs) to translate business needs into technical database structures.
• Optimize Performance: Tune data structures and database designs to improve system performance, query efficiency, and storage capacity.
• Data Governance & Quality: Enforce data quality standards, map data lineages, and ensure the security and privacy of sensitive company data.

Technical Requirements

• Data Modeling Tools: Proficiency in tools like Erwin Data Modeler, ER/Studio, or hackolade.
• Database Systems: Experience with relational databases (SQL Server, PostgreSQL, Oracle) and cloud data platforms (Snowflake, BigQuery, or AWS Redshift).
• Languages: Advanced knowledge of SQL for data analysis and schema generation.
• Methodologies: Strong understanding of Inmon (Normalized), Kimball (Dimensional/Star Schema), and Data Vault modeling techniques.

Soft Skills & Qualifications

• Analytical Thinking: Ability to dissect complex business processes and translate them into clean, structured data blueprints.
• Communication: Capable of explaining technical data architecture to non-technical business stakeholders.
• Education: A bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.

At least 5 years experience as a Data Modeler