Data Modeler (Azure Databricks)
* Only formal applications submitted with a CV will be considered. Direct messages and/or InMails will not be reviewed *** Rackspace Technology is a leading provider of expertise and managed services across all the major public and private cloud technologies.
Skills
About This Role
Overview
***** Only formal applications submitted with a CV will be considered.
Direct messages and/or InMails will not be reviewed *****
Rackspace Technology is a leading provider of expertise and managed services across all the major public and private cloud technologies.
We’ve evolved Fanatical Support to encompass the entire customer journey — providing Fanatical Experience™ from first consultation to daily operations.
Our passionate experts combine the power of proactive, always-on service and expertise with best-in-class tools and automation to deliver technology when and how our customers need it.
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.
***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).
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