Senior Data Modeler Consultant

Introduction: Design, implement, optimize enterprise data architecture and models that represent complex data using relational, dimensional, and NoSQL databases, and ensure data is structured for high performance, clarity, and long-term scalability across both operational and analytical systems.

Data Modeler will be the translator between business stakeholders and data engineering teams.

Assessment - Review current data models to understand the AS-IS environment.

Conceptual, Logical, and Physical Modeling - Plan, design and maintain blueprints of the TO-BE data models for OLTP (operational), OLAP (analytical), and Enterprise Data Lakehouse environments and how data will be stored, managed and used.

Business Alignment - Understand business processes and translate them into robust data requirements and review current report design documents to understand where data model structures can address business requirements.

Multi-Paradigm Modeling - Designing 3NF (Third Normal Form) for transactional databases, Dimensional Models (Kimball/Star Schema) for data warehousing, and Data Vault 2.0 for scalable enterprise data lakes.

Data Quality - Transform unstructured data into structured data by fixing errors, eliminate redundancies and unnecessary data to optimize data systems.

Performance Optimization - Optimize query performance through smart indexing, partitioning, and materialization strategies.

Data Governance - Establish, enforce and implement best practices, data naming standards, data definitions, maintain data maps and relevant diagrams for data systems and metadata management.

Data Security - Specify rules and guidelines for ensuring data security and compliance.

Define procedures for ensuring data are classified according to their sensitivity.

Tooling & Documentation - Maintain data schemas using modern standards modeling tools and ensure documentation is accessible to both technical and non-technical users.