Analytics Engineer

Lorien
Slough, UK
2 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Airflow Amazon Web Services Business Analytics Applications Data Analysis Business Logic Cloud Computing Continuous Integration Data Governance Data Systems Power BI Tableau (Software)
+8 more
Workflow Management Systems Sql Optimization Large Language Models Snowflake Git Data Layers Software Version Control Data Pipelines

Job description

  • Translate business requirements into well-structured data models, including conformed dimensions, facts, and metric definitions.
  • Design, build, and maintain transformation pipelines using dbt and Snowflake, orchestrated through Airflow.
  • Create and manage semantic models and metrics layers to ensure consistent reporting and analytics across the organisation.
  • Partner closely with business stakeholders to understand decision-making requirements and deliver data products that support self-service analytics.
  • Develop clean, governed datasets that can be reliably consumed by both users and AI/LLM-powered applications.
  • Migrate legacy reporting and embedded business logic into a centralised, governed data layer.
  • Champion analytics engineering best practices including testing, documentation, version control, and CI/CD.
  • Drive standards around data modelling, naming conventions, metrics management, and governance.
  • Mentor and support analysts and engineers in modern analytics engineering practices.

Technical Environment

  • Snowflake
  • dbt
  • Airflow
  • AWS
  • Semantic Layers / Metrics Frameworks
  • Tableau / Power BI
  • AI & LLM-enabled analytics solutions

Requirements

  • Advanced SQL skills with strong expertise in dimensional/Kimball modelling techniques.
  • Hands-on experience building and maintaining dbt models within Snowflake environments.
  • Experience orchestrating data pipelines using Airflow or similar workflow tools.
  • Proven experience creating semantic layers and metric models (e.g. dbt Semantic Layer, MetricFlow, Cube, LookML, AtScale, or similar).
  • Strong background delivering self-service analytics solutions.
  • Experience designing data products and models for AI/LLM consumption.
  • Regular use of AI-assisted development tools within engineering workflows.
  • Strong understanding of testing, Git-based version control, and CI/CD practices.
  • Proven ability to engage with stakeholders and translate business requirements into scalable data solutions.

Desirable Experience

  • Tableau and/or Power BI.
  • Experience supporting data consumption through applications and AI agents.
  • Data governance, cataloguing, and lineage tooling.
  • AWS cloud technologies.
  • Experience within operations, engineering, transport, or aviation environment

If you’re an Analytics Engineer who enjoys combining robust data modelling, modern cloud technologies, and AI-driven data solutions, we’d love to hear from you.

Apply for this position

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Apply on www.reed.co.uk
Prepare application

Good distractions

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