Senior Data Modeler Consultant

Design, implement, optimize enterprise data architecture and models that represent complex data using relational, dimensional, and No

SQL 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.

• B.Sc. Degree with a minimum of 5+ years of dedicated data modeling experience in enterprise relational databases, columnar databases.
• SQL Proficiency - Write, read, and optimize complex SQL transactional and analytical queries
• Modern Data Stack Familiarity - Experience modeling for cloud data warehouses/lake houses (e.g., SQLSERVER, Hadoop, Snowflake, Big Query, Databricks), working alongside transformation tools (e.g., dbt), and create ERDs for relational systems and dimensional diagrams.
• Tooling - Proficiency with ER/Studio, Erwin or similar data modeling software.
• No
  
  SQL/Unstructured Data - Understanding of when and how to model semi-structured data (JSON, Parquet) and No
  
  SQL databases (MongoDB, Cassandra) alongside relational data.
• Physical Data Management - Understand current data storage constrains and define TO-BE needs with growth allocation.
• Data Integration - Familiar with ETL tools to define the rules for data transformations and prepare data for big data analytics.
• Soft Skills:
  
  Communication, presentation skills, Business needs, able to lead or mentor a team.

Business Unit: DAIC

Level: Mid-senior level