Data Analytics Engineer, UK
Role Overview
The Data Analytics Engineer creates trusted, consistent and well-documented data products for BI, analytics, operational reporting and future AI-enabled use cases.
The role bridges data engineering, data architecture and BI, translating business rules, metrics and analytical needs into scalable models, semantic layers and reusable transformation logic.
The position is remote in the United Kingdom.
Key Skills for This Role
Full Job Posting
Role overview
The Data Analytics Engineer creates trusted, consistent and well-documented data products for BI, analytics, operational reporting and future AI-enabled use cases.
The role bridges data engineering, data architecture and BI, translating business rules, metrics and analytical needs into scalable models, semantic layers and reusable transformation logic.
The position is remote in the United Kingdom.
Responsibilities
- Work with business stakeholders, BI developers, analysts, data engineers and the data architect to define reusable 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.
- Build modular, transparent, version-controlled SQL transformations that are reusable and maintainable.
- Partner with data engineers to shape upstream pipelines, clarify source-to-target requirements and identify data quality issues early.
- Apply data tests, reconciliation checks, metric validation, documentation reviews and controlled releases.
- Maintain documentation of model definitions, lineage, business rules, ownership, limitations and appropriate use.
- Promote reusable data products, semantic modelling, automation, AI-ready foundations and reduced duplication across reporting.
Essential requirements
- Degree or equivalent experience in data, analytics, computer science or a related field.
- At least 5 years of data experience, including at least 2 years in analytics engineering, BI engineering or data modelling.
- Advanced SQL skills and experience building reusable, tested and documented transformation logic.
- Experience designing curated datasets, fact/dimension models or semantic datasets.
- Experience with a modern cloud data platform such as Microsoft Fabric, Synapse, Databricks, Snowflake or equivalent.
- Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
- Experience with Power BI or a similar BI tool and understanding of model impacts on reporting performance and usability.
- Ability to collaborate 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 with 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.
Stakeholders
Internal partners include BI and analytics, data engineering, data architecture, data governance and quality, business product owners, operational subject-matter experts, and technology operations and platform teams.
External relationships include data suppliers and partner organisations.
Competencies
The posting lists respect, effective partnership, innovative solutions, customer focus, compassion, responsibility, integrity, strategic business acumen, communication and data-driven decision-making among its competencies.
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