Analytics Engineer

Analytics Engineer

12-Month Contract | Inside IR35 | 2 Days Onsite at Heathrow

We're looking for an experienced Analytics Engineer to join a high-profile transformation programme, operating at the intersection of data engineering, analytics, and AI-enabled decision making.

This is a fantastic opportunity for someone who enjoys turning complex business challenges into scalable, trusted, and reusable data products. You'll play a key role in defining and building a governed semantic layer that enables self-service analytics, reporting, applications, and AI-driven solutions.

Key Responsibilities

• 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

Essential Skills & Experience

• 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