Senior Data Engineer

We are looking for Senior Data Engineer at London, UK – 2 days per week Onsite Security Clearance: Active SC Clearance is must have Job Description: • Development of data products such as data warehousing, data models, reporting, and business applications at scale to support improved business outcomes. • Provision of specialist skills in Microsoft BI Stack (Azure SQL, Fabric, Synapse Analytics, Power BI). • Understanding in Power Platform to deliver new business intelligence solutions and maintain existing solutions. • Analysis of data focusing on descriptive, diagnostic, and predictive analytics. • Provision of insights to inform decision-makers and other stakeholders. • Provision of a managed service to support projects and BAU activities. • Governance of data quality across systems to ensure high standards are achieved and maintained, providing high levels of assurance. Technical Skills: • ETL/ELT development using tools such as Azure Data Factory. • Extensive experience with SQL Server and Data Warehousing. • Strong understanding and experience working with Microsoft Fabric. • Experience working with large and complex datasets. • Data Modelling and Design expertise. • Basic DBA skills. • Report development in Power BI. • Experience with data lake and cloud data warehousing. • ServiceNow experience is an advantage. • Code version control via GitHub or similar would be an advantage. • CI/CD experience would be an advantage. • Microsoft certification in Fabric or Power BI is an advantage. Key Responsibilities: As a Senior Data Engineer, you will: • Implement data flows to connect operational systems, analytics platforms, and business intelligence (BI) systems. • Document source-to-target mappings and define data architecture. • Re-engineer manual data flows to enable scalability and reusability. • Support the build of data streaming and batch processing systems. • Write ETL (extract, transform, load) scripts and code to ensure optimal ETL performance. • Develop reusable business intelligence reports and dashboards. • Build accessible and governed data solutions for analysis. • Recognise opportunities to reuse existing data flows and optimise processes. • Lead the implementation of data streaming solutions and best practices. • Optimise code and ensure high-performance data processing. • Lead work on database management, ensuring security, scalability, and reliability. Person Specification (Essential) • Communicating between the technical and non-technical: Effectively communicate with stakeholders across various technical and business functions. Support and facilitate discussions within multidisciplinary teams while managing differing perspectives. • Data analysis and synthesis: Conduct data profiling and source system analysis. Present clear insights to support data-driven decision-making. • Data development process: Design, build, and test complex and large-scale data products. Lead teams to complete data integration services. • Data innovation: Stay updated on emerging trends in data tools, analysis techniques, and data usage to drive innovation. • Data integration design: Select and implement the appropriate technologies to deliver resilient, scalable, and future-proofed data solutions. • Data modelling: Produce relevant data models across multiple subject areas. Understand and apply industry-recognised data modelling patterns and standards. • Metadata management: Design and maintain metadata repositories, ensuring effective storage and management of metadata assets. • Problem resolution (data): Diagnose and resolve data-related issues in databases, data processes, and services. Implement preventative measures to enhance data reliability. • Programming and build (data engineering): Use best practices to design, code, test, and document programs and scripts. Collaborate with teams to refine requirements and specifications. • Technical understanding: Apply core technical concepts to design and optimise data solutions.