Data Analytics Engineer, UK

Maximus U.K.
UK
27 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours
Job source

Tech stack

Training Data Adaptable Database Systems Agile Methodology Artificial Intelligence Data Analysis Business Intelligence Development Data as a Services Data Architecture Data Validation Information Engineering Data Governance Decision Support Systems
+15 more
Machine Learning Metadata Power BI SQL Databases Sql Optimization Snowflake Data Layers Microsoft Fabric Information Technology Data Analytics Data Management Azure Synapse Analytics Software Version Control Data Pipelines Databricks

Job description

  • Create trusted, consistent, well-modelled and clearly documented data products for BI, analytics, operational reporting and future AI-enabled use cases, with a strong focus on reusability.
  • Bridge the gap between data engineering, data architecture and BI teams by translating business rules, metrics and analytical requirements into scalable data models, semantic layers and reusable transformation logic.
  • Improve trust, speed and consistency in decision-making by applying modern analytics engineering practices, including version control, testing, documentation, data quality checks and clear ownership of shared business definitions.
  1. Work with business stakeholders, BI developers, analysts, data engineers and the data architect to translate reporting and decision-making needs into clear, reusable analytics requirements and data product specifications.
  2. Design, build and maintain analytics-ready data models, including curated datasets, fact and dimension models, reusable metric logic and semantic structures that support consistent self-service analytics.
  3. Develop modular transformation logic using SQL and modern analytics engineering approaches, ensuring business rules are transparent, version controlled, reusable and easy to maintain as organisational needs change.
  4. Partner with data engineers to shape upstream data pipelines, clarify source-to-target requirements, identify data quality issues early, and ensure engineered data services are fit for downstream analytics consumption.
  5. Implement analytics quality controls, including data tests, reconciliation checks, metric validation, documentation reviews and controlled releases to improve trust in reports, dashboards and analytical outputs.
  6. Create and maintain clear data product documentation, including model definitions, lineage, business rules, ownership, known limitations and appropriate usage guidance for BI, analytics and operational teams.
  7. Champion forward-looking analytics engineering practices, including reusable data product design, semantic modelling, automation, AI-ready data foundations and the reduction of duplicated logic across reports and teams.

Key Internal Stakeholders & Relationships

  • BI and Analytics Team
  • Data Engineering Team
  • Data Architect
  • Data Governance and Data Quality Teams
  • Business Product Owners and Operational SMEs
  • Technology Operations and Platform Teams

Key External Stakeholders & Relationships

  • External data suppliers
  • Partner organisations

Requirements

  • Degree or equivalent experience in data, analytics, computer science or a related field.
  • 5+ years in data, including 2+ years in analytics engineering, BI engineering or data modelling.
  • Advanced SQL skills, with experience building reusable, tested and 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.
  • Good understanding of data quality, lineage, governance, privacy and access control in analytical environments.
  • Experience working with Power BI or similar BI tools, including how model design affects reporting performance and usability.
  • Confident working with data engineers, data architects, BI teams and business stakeholders to deliver trusted data products.
  • Experience with dbt, SQLMesh, Fabric semantic models or equivalent analytics engineering tools.

Desirable

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

Maximus Competencies

  • Embraces Respect.
  • Partners Effectively:
  • Creates Innovative Solutions
  • Focuses on the Customer:
  • Demonstrates Compassion.
  • Takes Responsibility & Acts with Integrity

Individual competencies

  • Strategic Business Acumen, Exceptional Communication, Data-Driven Decision Making.
  • Growth-Orientated Mindsets, Solution focused, Detail-Orientes, Proactive and Agile Execution: Results Drivel, Adaptive Leadership, Learning Agility, Emotionally Intelligent Leadership

About the company

Maximus is a global organisation that specialises in providing health and employment services to millions of people every year. Here in the UK we employ around 5,000 people across the country to deliver services that have a profound impact on people’s lives. From assessments and health services to employability programmes and specialist support, we do work that matters with people who care.

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