Data Analytics Engineer, UK

Role overview

Key responsibilities

• Translate stakeholder reporting and decision-making needs into reusable analytics requirements and data product specifications.
• Build and maintain curated datasets, fact and dimension models, reusable metric logic, and semantic structures for self-service analytics.
• Develop modular SQL transformations that are version-controlled, tested, reusable, transparent, and maintainable.
• Work with data engineers on pipelines, source-to-target requirements, early data quality identification, and downstream analytics readiness.
• Apply tests, reconciliation checks, metric validation, documentation reviews, and controlled releases.
• Document data models, lineage, business rules, ownership, limitations, and appropriate usage.
• Promote reusable data products, semantic modelling, automation, AI-ready foundations, and reduced duplication across reports.

Essential qualifications and experience

• Degree or equivalent experience in data, analytics, computer science, or a related field.
• At least 5 years in data, including 2 or more years in analytics engineering, BI engineering, or data modelling.
• Advanced SQL and experience building reusable, tested, well-documented transformations.
• Experience with analytics-ready models and a modern cloud data platform such as Microsoft Fabric, Synapse, Databricks, Snowflake, or equivalent.
• Understanding of data quality, lineage, governance, privacy, and access control.
• Experience with Power BI or a similar BI tool and analytics engineering tools such as dbt, SQLMesh, Fabric semantic models, or equivalent.

Desirable experience

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

Stakeholders and competencies