2 of 2 Contract Azure Data Factory Jobs in the City of London

/day (Inside IR35) Databricks Engineer needed with active SC Security Clearance for 6 Month Contract based in Central London (Hybrid). Developing a cutting-edge Azure Databricks platform for economic data modelling, analysis, and forecasting. Start ASAP in Dec 2025. Hybrid Working - 2 days/week remote (WFH), and 3 days/week working on … site from the Central London office. A chance to work with a leading global IT and Digital transformation business specialising in Government projects: In-depth Data Engineering + strong hands-on Azure Databricks expertise. Azure Data Services, Azure Data Factory, Azure Blob Storage + … Azure SQL Database. Designing, developing, building + optimising data pipelines, implementing data transformations, ensuring data quality and reliability. Deep Data Warehousing knowledge including data modelling techniques + data integration patterns. Experience of working with complex data pipelines, large data sets, data More ❯

Azure Data Engineer - £400PD - Remote Seeking an experienced Data Engineer to design, build, and optimise data solutions within the Microsoft Azure ecosystem. The role focuses on pipeline development, data modelling, governance, and supporting analytics teams with high-quality, reliable data. Key Responsibilities: Develop and maintain scalable data pipelines using Azure Data Factory, Synapse, Databricks, and Microsoft Fabric. Build efficient ETL/ELT processes and data models to support analytics, reporting, and dashboards. Optimise existing pipelines for performance, reliability, and cost efficiency. Implement best practices for data quality, error handling, automation, and monitoring. Manage data security and governance, including Row-Level Security (RLS) and compliance standards. Maintain documentation and metadata for data assets and pipeline architecture. Collaborate with analysts, data scientists, and stakeholders to deliver trusted data products. Provide technical support and troubleshoot production issues. Contribute to improving data engineering processes and development lifecycle. Required More ❯