Data Modeler – Azure Databricks (Medallion Architecture) - RAXJP00002194 - Dubai

About This Role

Position: 1 Duration: 12 months Location: Dubai Address:

3, Al Rigga road Al Muraqqabat, Deira, Dubai Level 7 Working Hours/Time Zone: 8 hrs/day, UAE time (following the UAE labour law) Onsite/Remote: Onsite interview process: All profiles will go through online test, only the candidates who cleared the test will go through the 2 rounds of interview - 1- Internal Technical discussion, 2- Client Technical discussion. Bill Rate: USD 20-22/hr -

This will be the only rate accepted Top 3 requirements: Strictly follow the JD shared, Worked as a data modeller (must have - more than 8+ experience as data modeller), clear understanding on the data modelling concepts, has experience on implementing the data modelling in Lakehouse projects.

Job Description: 8+ yrs of Data Modelling experience.

Data Modeler - Azure Databricks (Medallion Architecture)

Role Purpose

Design and deliver implementation-ready logical and physical data models within Azure Databricks (Delta Lake) following Medallion Architecture (Bronze, Silver, Gold).

The role ensures Data Engineers can immediately begin development with clear schema definitions, SQL structures, and zero ambiguity.

Key Responsibilities

• Data Modelling & Design
• Develop Conceptual, Logical, and Physical Data Models.
• Define schemas, entities, attributes, relationships, keys, constraints, and data types.
• Provide DDL-ready SQL definitions for implementation.
• Clearly define fact table grain and dimensional structures.
• Azure Databricks - Medallion Modelling
• Design structured models across:

○ Bronze Layer - Raw ingestion, schema control.

○ Silver Layer - Cleansed, conformed, standardized data.

○ Gold Layer - Business-ready dimensional models.

Data Modeler - Azure Databricks (Medallion Architecture)

• Define transformation logic across layers (Bronze → Silver → Gold).
• Incorporate Delta Lake best practices (partitioning, performance, scalability).
• Advanced Modelling Techniques

Strong hands-on expertise in:

• 3rd Normal Form (3NF)
• Star Schema
• Snowflake Schema
• Data Vault (Hubs, Links, Satellites)

Must clearly define:

• Fact grain
• Surrogate key strategy
• Slowly Changing Dimensions (Type 1 & 2)
• Conformed dimensions
• Aggregation strategy
• Engineering & Governance Alignment
• Ensure models are build-ready for Data Engineering teams.
• Review implementation alignment with design.
• Maintain ER diagrams, data dictionary, mapping documents.
• Enforce enterprise naming standards and modelling best practices.

Required Skills & Experience

• 8+ years of hands-on Data Modelling experience.
• Strong SQL (DDL, partitioning, performance concepts).
• Proven experience in Azure Databricks and Delta Lake environments.
• Deep understanding of Medallion Architecture.
• Experience in enterprise Data Warehouse or Modern Data Platform projects.
• Proficiency with data modelling tools (ERwin, ER Studio, PowerDesigner, Lucidchart, or similar).