Data Modeler

Position Overview

Data Modeler

Key Responsibilities

• Design and develop

  Conceptual, Logical, and Physical Data Models

  based on business requirements, ensuring alignment with data governance and architectural standards.
• Collaborate with business analysts, data engineers, and stakeholders to translate business needs into scalable and maintainable data structures.
• Perform

  data design, model design, and data profiling

  to ensure data quality, consistency, and integrity across multiple systems.
• Work with different modeling methodologies including:

• 3NF (Third Normal Form)

  for operational data stores.

• Data Vault modeling

  for scalable, auditable enterprise data warehouses.

• Common Data Model (CDM)

  for standardized data representation across applications.

• Industry domain models

  (e.g., finance, healthcare, retail) to ensure semantic consistency.
• Design and support implementation of

  Medallion Architecture (Bronze, Silver, Gold layers)

  in modern data platforms such as Microsoft Fabric, Azure Synapse, or Databricks.
• Define and maintain

  metrics and attributes

  for analytical models and ensure proper dimensional modeling for BI and reporting solutions.
• Support

  forward and reverse engineering

  processes to generate physical databases from logical models and derive models from existing databases.
• Collaborate with development teams to ensure model changes are properly implemented and version-controlled.
• Participate in performance tuning and optimization of database structures.
• Maintain documentation and metadata for all data models, ensuring compliance with data governance and architectural best practices.

Technical Skills Required

• Strong expertise in

  Conceptual, Logical, and Physical Data Modeling

  .
• Hands-on experience in

  Data Design, Data Profiling

  , and

  Normalization/Denormalization techniques

  .
• Practical knowledge of

  Data Vault

  ,

  3NF

  , and

  Dimensional Modeling

  .
• Good understanding of

  Medallion Architecture

  (Bronze, Silver, Gold Layers) and its role in data pipelines.
• Familiarity with

  Common Data Model (CDM)

  and

  Industry Domain Models

  .
• Understanding of

  Forward Engineering

  (creating databases from models) and

  Reverse Engineering

  (deriving models from existing databases).
• Experience with at least one

  Data Modeling Tool

  such as

  Erwin Data Modeler

  ,

  PowerDesigner

  , or

  SQL Data Modeler

  .

• Basic to intermediate proficiency in Erwin Data Modeler

  , including schema generation, version control, and metadata management.
• Familiarity with relational databases (e.g., Oracle, SQL Server, PostgreSQL) and cloud-based data platforms (e.g., Azure Synapse, MS Fabric, Snowflake).