Data Modeler

شرح موقعیت

Role Summary Trusted analytics and AI depend on data that is structured consistently, described unambiguously and traceable to the business it represents. The Data Modeler owns the conceptual, logical and physical data models across the lakehouse, translating business concepts into models that are performant, governed and stable over time. The role works alongside the Data Architect, business analysts, data engineers, data stewards and the Senior Data Quality Engineer. Its job is to make sure every table, key and attribute in the platform is designed to standard, documented in Microsoft Purview, and aligned to the business glossary and Critical Data Elements. Key Responsibilities on the Client’s Engagement Conceptual and logical modelling: Work with business analysts and data owners to define subject areas, entities, relationships, business keys and definitions, and capture them in conceptual and logical data models. Physical modelling for the lakehouse: Design physical models for the Silver (conformed) and Gold (curated) layers, including dimensional (star/snowflake) models, data marts and, where appropriate, Data Vault structures. Modelling standards: Apply and maintain the program's modelling standards for naming, data types, surrogate and business keys, normalizations, referential integrity, historization and Slowly Changing Dimensions (SCD). Source-to-target mapping: Produce and maintain source-to-target mappings and transformation rules that data engineers implement and the QA and DQ teams validate against. Master and reference data models: Define master and reference data entity models, hierarchies and code sets, and align them with the MDM platform and golden-record design. Semantic layer: Design the semantic model, measures, hierarchies and KPI definitions for Power BI and analytics consumption, in line with agreed business rules. Metadata and glossary alignment: Publish models, definitions and relationships to Microsoft Purview and keep them aligned to the business glossary and Critical Data Elements. Model governance and change control: Version and review model changes, assess downstream impact, and secure sign-off through the architecture and data governance forums. Data classification support: Tag attributes with classification, sensitivity and PII markers so that access, masking and retention controls can be enforced in line with UAE PDPL, the Dubai Data Law and DESC ISR. Knowledge transfer: Coach SUTHERLAND analysts and engineers in modelling standards and tooling so that models can be extended consistently after handover. Qualifications and Experience 6+ years in data modelling on data warehouse, lakehouse or analytics programs, preferably within UAE government or regulated-sector environments. Expert in conceptual, logical and physical modelling, including dimensional (Kimball) design, normalizations, Data Vault and canonical models. Strong SQL skills and a working understanding of how models are implemented in Spark/Delta on Azure / Microsoft Fabric, Databricks or Synapse. Hands-on experience with modelling tools such as Erwin, ER/Studio, SqlDBM or equivalent, and with publishing models to Microsoft Purview. Understanding of master and reference data modelling, semantic layers and Power BI data models. Familiarity with DAMA-DMBOK2 and UAE data regulation, including UAE PDPL, Dubai Data Law and DESC ISR. Certifications such as DAMA CDMP or Fabric Analytics Engineer are an advantage. Excellent English communication and documentation skills; Arabic proficiency is an advantage given bilingual data and stakeholders.