Senior Data Analytics Engineer

scrumconnect ltd; City of Westminster; On-site; GBP 70,000 - 95,000; Full time

Benefits offered by this job

Exposure to public sector programmes

Collaborative culture

Job summary

Scrumconnect Consulting, a digital and data consultancy, seeks a Senior Data Analytics Engineer to design, build and maintain robust analytical data assets for complex public sector domains. You will work hands-on with analytics engineers, data engineers and analysts, delivering scalable data models and reusable datasets.

Responsibilities include stakeholder engagement, requirement gathering, and implementing metadata, quality controls and best practices across data solutions.

Qualifications

• Strong experience as an Analytics Engineer or similar data-focused role.
• Proven experience designing dimensional data models for analytics.
• Hands-on with dbt and modern analytics practices.

Responsibilities

• Design and maintain flexible dimensional data models for analytics and reporting.
• Collaborate with stakeholders to translate requirements into deliverables.
• Work with dbt and Airflow to deploy data solutions.
• Ensure data quality and metadata management across datasets.

Skills

Analytics engineering

Dimensional modeling

dbt

Airflow

Stakeholder management

Tools

dbt

Airflow

Cloud platforms

Job description

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 with stakeholders across complex domains, including GDS-aligned programmes, to understand data relationships and business processes, and turn them into robust analytical data assets. This role is hands-on technical delivery with strong stakeholder engagement. You will work closely with other Analytics Engineers, Data Engineers and Analysts. It does not include line management or team leadership., Stakeholder engagement and requirements

Stakeholder engagement and requirements

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

Data modelling and analytics engineering

• Design, build and maintain flexible, quality-assured dimensional data models for analytics and reporting.
• Build and review complex data models using tools such as dbt, keeping to agreed standards and best practice.
• Integrate and model data from complex source systems, combining multiple sources into conformed analytical models.
• Make sure data models work with other datasets to support reuse and scalability.

Metadata, quality and standards

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

Collaboration and continuous improvement

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

Key Deliverables

• Clear analytical data requirements, turned 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.
• Better metadata capture, storage and presentation, enabling intelligent and responsible data use.
• Consistent application of data modelling standards, documentation and best practice.

Essential

• SC cleared (first preference) or SC eligible.
• 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.
• Able to communicate effectively with technical and non-technical stakeholders.

Desirable

• Experience in 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.

Scrumconnect Consulting is a digital and data consultancy delivering high-quality technology, analytics and transformation services to public and private sector clients. We work closely with government departments and complex organisations to design and deliver scalable, ethical and impactful data solutions.

At Scrumconnect, we are more than just a consultancy. We are a collaborative team focused on delivering impactful digital transformation services across government and enterprise organisations.

As part of our team, you will benefit from:

• Exposure to major public sector digital and data programmes.
• A collaborative and inclusive working culture.
• Hands‑on experience working within agile delivery environments.