Data Modeler

Position: Data Modeler

Duration: 12 months

Location: Dubai Address: Al Rigga road Al Muraqqabat, Deira, Dubai

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.

Top 3 requirements: Strictly follow the JD shared, Worked as a data modeller (must have - more than 1yr experience as data modeller), clear understanding on the data modelling concepts, has experience on implementing the data modelling in Lakehouse projects.

Job Description:

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

1. 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.

2. 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).

3. 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

4. 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

5+ 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).