Robert Half is supporting a Global Consulting Firm in recruiting a Data Warehouse Developer / Data Engineer for a critical role within a major data & analytics programme in the insurance sector. This project involves designing and implementing high-performing, scalable data warehouse solutions to enhance business intelligence and analytics capabilities across the organisation. The ideal candidate will possess strong experience with the Kimball methodology, dimensional modelling, SQL, hands-on experience with Azure Data Factory, Fabric, and Power BI.

Assignment Details:

• Location: Remote with 1-2 days on-site in Leeds
• Duration: Initial 6-month contract
• Day Rate: £450 per day via an FCSA Accredited umbrella company
• Start Date: Immediate, with 1-2 weeks for onboarding and setup

Experience Required:

• Extensive experience in data warehousing and data engineering, particularly using the Kimball methodology and dimensional modelling to create efficient data structures for reporting and analytics.
• Advanced SQL skills and expertise in ETL processes, with a focus on high performance, scalability, and data reliability.
• Hands-on experience with Azure Data Factory, Fabric, and Power BI for end-to-end data integration, transformation, and visualisation, ideally within insurance or financial environments.
• Proven ability to ensure data accuracy, integrity, and consistency across complex data environments.
• Strong collaboration skills with a track record of effective engagement with business analysts, data engineers, and other key stakeholders.

Key Responsibilities:

• Data Warehouse Design & Development: Develop and implement data warehouse solutions using the Kimball methodology, focusing on dimensional data models to meet reporting and analytics needs.
• ETL Processes: Design, optimise, and manage ETL workflows, leveraging Azure Data Factory for high-performance data integration and transformation.
• Data Visualisation with Power BI: Create intuitive and insightful data visualisations in Power BI, enabling stakeholders to derive actionable insights from the data warehouse.
• Data Quality & Performance: Ensure data accuracy and consistency within the data warehouse to enable reliable business intelligence efforts.
• Documentation: Create and maintain comprehensive documentation for warehouse architecture, ETL processes, and best practices to ensure continuity and ease of understanding.
• Stakeholder Collaboration: Engage closely with business analysts, data engineers, and other stakeholders to gather data requirements and deliver tailored, effective solutions.

Important Note:

Candidates will undergo comprehensive financial and criminal background checks, which may take up to two weeks to complete.

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