Senior Data Analytics Engineer (SC Cleared)

As a Senior Data Analytics Engineer, you will play a critical role in designing, building, and maintaining high-quality data models that enable analytics, reporting, and data-driven decision-making. You will work closely with stakeholders across complex domains (including GDS-aligned programmes) to understand data relationships and business processes, translating these into robust analytical data assets. This role focuses on hands‑on technical delivery and stakeholder engagement. While you will collaborate closely with other Analytics Engineers, Data Engineers, and Analysts, this role does not include line management or team leadership responsibilities.

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• Work with stakeholders and delivery teams across the GDS-aligned programmes and complex public‑sector domains to understand business processes, data relationships, and analytical needs.
  
• Interpret the needs of both technical and non‑technical stakeholders and manage expectations through clear, proactive, and reactive communication.
  
• Gather user requirements and translate them into clear, actionable, and deliverable tasks.
  
• Act as a key point of contact for analytical user communities, supporting adoption and effective use of analytical data products.
  

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• Design, build, and maintain flexible, quality‑assured dimensional data models for analytical and reporting use.
  
• Build and review complex data models using tools such as dbt, ensuring adherence to agreed standards and best practices.
  
• Integrate and model data from complex source systems, including combining multiple data sources into conformed analytical models.
  
• Ensure data models are interoperable with other datasets to support reuse and scalability.
  

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• Design and contribute to appropriate metadata repositories, suggesting improvements to existing metadata management approaches.
  
• Use a range of tools for storing, managing, and working with metadata.
  
• Ensure analytical data meets defined data quality standards.
  
• Apply and support data profiling techniques to assess data completeness, accuracy, and reliability.
  
• Review data models and documentation to ensure consistency with standards and best practice.
  

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• Work closely with Data Engineers to support end‑to‑end data services and deploy solutions in a reproducible and sustainable way.
  
• Collaborate with other data professionals to improve modelling, integration patterns, and analytics engineering standards.
  
• Support analytical teams to use modelled data effectively by enabling access to well‑documented, well‑governed data.
  
• Enable automation and adoption of modern analytics tools such as dbt and Airflow.
  

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• Clear, well‑defined analytical data requirements translated into deliverable tasks.
  
• High‑quality dimensional data models built and maintained using dbt.
  
• Well‑documented, quality‑assured analytical datasets ready for reporting and advanced analytics.
  
• Improved metadata capture, storage, and presentation to enable intelligent and responsible data use.
  
• Consistent application of data modelling standards, documentation, and best practices.
  

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• Strong experience as an Analytics Engineer or in a similar data‑focused role.
  
• Proven experience designing and building dimensional data models for analytics and reporting.
  
• Hands‑on experience with dbt and modern analytics engineering practices.
  
• Experience working with complex data sources and integrating multiple systems into conformed models.
  
• Strong understanding of data quality, metadata management, and data profiling techniques.
  
• Ability to communicate effectively with both technical and non‑technical stakeholders.
  

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• Experience working within government or public‑sector data environments aligned to GDS standards.
  
• Experience with orchestration tools such as Airflow.
  
• Familiarity with cloud‑based data platforms and modern data stacks.
  
• Understanding of data governance and ethical data use in regulated environments.