Data Modeler (Azure Databricks)

*** Only formal applications submitted with a CV will be considered. Direct messages and/or InMails will not be reviewed ***

Rackspace Technologytrade mark is a leading end-to-end, hybrid cloud and AI solutions company. We can design, build, and operate our customers cloud environments across all major technology platforms, irrespective of technology stack or deployment model. We partner with our customers at every stage of their cloud journey, enabling them to modernize applications, build new products, and adopt innovative technologies. Named a best place to work by Glassdoor, Newsweek and Forbes, we attract and develop world-class talent to deliver a Fanatical Experiencetrade mark – so our customers can achieve better outcomes and stay ahead of what's next.

As a Data Modeler, you will 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:
• o Bronze Layer – Raw ingestion, schema control.
• o Silver Layer – Cleansed, conformed, standardized data.
• o Gold Layer – Business-ready dimensional models.

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

Advanced Modelling Techniques.

Requires 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:

• 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).