Data Analytics Engineer, UK

Role overview

Workplace

• The role is remote in the United Kingdom.

Responsibilities

• Work with business stakeholders, BI developers, analysts, data engineers, and the data architect to define analytics requirements and data product specifications.
• Design and maintain curated datasets, fact and dimension models, reusable metric logic, and semantic structures for self-service analytics.
• Develop modular, reusable, version-controlled SQL transformation logic.
• Partner with data engineers on upstream pipelines, source-to-target requirements, and data quality for downstream analytics.
• Implement data tests, reconciliation checks, metric validation, documentation reviews, and controlled releases.
• Document model definitions, lineage, business rules, ownership, known limitations, and usage guidance.
• Promote reusable data products, semantic modelling, automation, AI-ready foundations, and reduced duplicated logic.

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, documented transformations and analytics-ready models.
• Experience with cloud data platforms such as Microsoft Fabric, Synapse, Databricks, Snowflake, or equivalent.
• Experience with Power BI or similar BI tools and with dbt, SQLMesh, Fabric semantic models, or equivalent.
• Knowledge of data quality, lineage, governance, privacy, and access control.
• Ability to work with data engineering, architecture, BI, and business stakeholder teams.

Desirable experience

• Governed data products in regulated or complex environments are desirable.
• Data catalogue, lineage, metadata, or business glossary tools are desirable.
• Exposure to AI-ready datasets, advanced analytics, or machine learning use cases is desirable.

Competencies

• The posting lists respect, effective partnership, innovative solutions, customer focus, compassion, responsibility, and integrity.
• Individual competencies include strategic business acumen, communication, data-driven decision-making, growth orientation, solution focus, attention to detail, proactive execution, adaptability, and learning agility.