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.