Data Analytics Engineer, UK

Role overview

Responsibilities

• Create consistent, well-modelled, clearly documented data products for BI, analytics, reporting, and future AI-enabled use cases.
• Translate business rules, metrics, and analytical requirements into scalable data models, semantic layers, and reusable transformation logic.
• Convert reporting and decision-making needs into reusable analytics requirements and data product specifications with stakeholders and technical teams.
• Design, build, and maintain curated datasets, fact and dimension models, reusable metric logic, and semantic structures.
• Develop modular SQL transformation logic that is transparent, version-controlled, reusable, and maintainable.
• Partner with data engineers on upstream pipelines, source-to-target requirements, data quality issues, and downstream analytics readiness.
• Implement data tests, reconciliation checks, metric validation, documentation reviews, and controlled releases.
• Document model definitions, lineage, business rules, ownership, known limitations, and appropriate usage.
• Promote reusable data product design, semantic modelling, automation, AI-ready foundations, and reduced duplication across reports.

Essential requirements

• Degree or equivalent experience in data, analytics, computer science, or a related field.
• At least 5 years in data, including at least 2 years in analytics engineering, BI engineering, or data modelling.
• Advanced SQL skills and experience building reusable, tested, well-documented transformation logic.
• Experience designing analytics-ready models, including curated datasets, fact/dimension models, or semantic datasets.
• Experience with modern cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake, or equivalent.
• Understanding of data quality, lineage, governance, privacy, and access control in analytical environments.
• Experience with Power BI or similar BI tools and how model design affects reporting performance and usability.
• Ability to work with data engineers, data architects, BI teams, and business stakeholders.
• Experience with dbt, SQLMesh, Fabric semantic models, or equivalent analytics engineering tools.

Desirable experience

• Experience building governed data products in regulated or complex environments is desirable.
• Experience with data catalogues, lineage, metadata, or business glossary tools is desirable.
• Exposure to AI-ready datasets, advanced analytics, or machine learning use cases is desirable.

Key working relationships