Senior Dimensional Modeling Specialist

Job Title: Senior Dimensional Modeling Specialist

Location:
United Arab Emirates (Remote) Employment Type: Full-Time Work Arrangement: 100% Remote — Work From Home Level: Senior

About the Role
We are seeking an experienced Senior Dimensional Modeling Specialist to design, develop, and optimize analytical data models that support enterprise reporting, business intelligence, and data warehousing initiatives.

The role focuses on translating complex business requirements into reliable dimensional structures, improving data consistency, and enabling efficient analytical queries across organizational data platforms.

This fully remote position requires strong expertise in dimensional modeling methodologies, data warehouse architecture, fact and dimension design, data integration, and analytical database performance. The specialist will collaborate with data engineers, architects, business analysts, and reporting teams to deliver scalable, well-governed data models that support accurate business insights.

Key Responsibilities

Design and maintain dimensional data models using established methodologies, including star schemas and snowflake schemas. Translate business reporting requirements into logical and physical dimensional models. Define fact tables, dimension tables, measures, hierarchies, attributes, and business keys. Determine appropriate fact table grain and ensure consistency across related analytical datasets. Design and implement slowly changing dimensions, including appropriate handling of historical attributes and changes over time.

Develop conformed dimensions and reusable data structures to support consistent reporting across business domains. Establish relationships between transactional source systems, staging layers, data warehouses, and analytical data marts. Collaborate with data engineering teams to define transformation logic, data integration requirements, and model dependencies. Review source data structures and identify inconsistencies, duplication, missing attributes, and data quality risks.

Define surrogate key strategies, natural key mappings, and referential integrity requirements. Optimize dimensional models for query performance, storage efficiency, scalability, and maintainability. Review SQL queries, execution plans, and warehouse performance metrics to identify modeling-related bottlenecks. Develop and maintain data dictionaries, model specifications, business definitions, and technical documentation. Establish naming conventions, modeling standards, metadata requirements, and reusable design patterns.

Support semantic layer development by defining business measures, dimensions, aggregation rules, and calculation logic. Validate dimensional models against business requirements and expected analytical outcomes. Coordinate model testing, reconciliation, and data quality assessments with engineering and reporting teams. Assess the impact of source system changes on existing dimensions, facts, reports, and downstream analytical processes.

Support data warehouse modernization, platform migration, and analytical architecture improvement initiatives. Provide technical guidance and mentoring to data modelers, data engineers, and business intelligence developers.

Qualifications and Experience

Bachelor's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related discipline. Significant professional experience in data modeling, data warehousing, business intelligence, or enterprise analytics. Strong understanding of dimensional modeling principles, including star schemas, snowflake schemas, fact tables, and dimension tables. Practical experience defining fact table grain, conformed dimensions, surrogate keys, and historical data management strategies.

Strong knowledge of slowly changing dimensions, including Types 1, 2, and 3. Advanced SQL skills, including complex joins, aggregations, window functions, and query optimization. Experience with enterprise data warehouse platforms such as Snowflake, Amazon Redshift, Google BigQuery, Microsoft Fabric, Azure Synapse, or comparable technologies. Familiarity with data integration and transformation tools such as dbt, Informatica, Talend, Microsoft SSIS, or equivalent platforms.

Experience with data modeling tools such as ER/Studio, erwin Data Modeler, SAP PowerDesigner, or comparable solutions. Understanding of ETL and ELT processes, data lineage, metadata management, and data quality frameworks. Knowledge of analytical reporting platforms and semantic modeling concepts. Ability to interpret complex business requirements and convert them into practical, scalable data structures. Strong analytical and problem-solving skills, with attention to data accuracy and consistency.

Excellent technical documentation, communication, and cross-functional collaboration skills. Ability to manage multiple modeling initiatives and work independe