SC Cleared Data Warehouse Engineer - Outside IR35 - Remote

We are seeking a skilled Data Warehouse Engineer to design, build, and maintain scalable data warehouse solutions within the Microsoft Azure ecosystem. The role focuses on developing robust data models, optimizing analytical queries, and supporting enterprise reporting through Azure SQL, OLAP technologies, and DAX-powered semantic models.

You will collaborate with data engineers, analysts, and business stakeholders to ensure reliable, high-performance data pipelines and analytics platforms.

• Design and develop enterprise data warehouse solutions using Azure SQL Database / Azure SQL Managed Instance / Azure Synapse Analytics.

• Build and maintain star and snowflake schemas for analytical workloads.

• Develop ETL/ELT pipelines for ingesting and transforming data from multiple source systems.

• Implement data partitioning, indexing, and performance optimization strategies.

• Develop OLAP data models for business intelligence and reporting.

• Create and optimize DAX measures, calculated columns, and KPIs.

• Design semantic models for Power BI or Analysis Services.

• Ensure high performance for large analytical datasets.

• Work with Azure data services to design scalable data architecture.

• Ensure data quality, governance, and security controls.

• Support data integration with operational systems, APIs, and third-party data sources.

• Implement monitoring and performance tuning for warehouse workloads.

• Strong experience with Azure SQL (T-SQL, performance tuning, indexing, partitioning).

• Experience building enterprise data warehouses.

• Expertise in OLAP data modeling.

• Advanced knowledge of DAX (Data Analysis Expressions).

• Experience with Power BI semantic models or Azure Analysis Services / SQL Server Analysis Services (SSAS).

• Strong data modeling skills (star schema, dimensional modeling).

• Experience with:

  • Azure Synapse Analytics

  • Azure Data Factory or similar ETL tools

  • Azure Storage / Data Lake

• Experience designing data pipelines and transformations.

To apply for this role please submit your CV or contact Dillon Blackburn on or at .

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