Data Modelling & Product Development (50%) : Design, build and maintain scalable, reusable and well-documented data models and curated datasets that support analytics, BI, product and data science use cases. Translate complex raw data into trusted, business-aligned datasets.
Data Quality, Testing & Documentation (25%) : Implement robust testing frameworks and automated checks to ensure data accuracy, consistency and reliability. Maintain clear documentation and improve discoverability of datasets and metrics.
Business Partnership & Metric Definition (25%) : Work closely with Analytics, Product, Data Science and commercial teams to define and align on KPIs, business logic and data definitions. Ensure datasets support consistent decision-making across the organisation.
What You'll Love About This Role
Think Big: Help build foundational analytics models and standards for a next-generation AI-driven intelligence platform.
Own It: Take responsibility for trusted datasets and business logic that underpin key commercial and product decisions.
Keep it Simple: Turn complex, messy data into clear, reusable and well-structured data products.
Better Together: Collaborate across Data Engineering, Product, Analytics and Commercial teams to solve real-world problems.
What Success Looks Like
In your first few months, you'll have:
Built a strong understanding of the Global:IQ vision and key use cases
Delivered curated datasets supporting key targeting, optimisation or measurement needs
Established consistent business logic, definitions and KPIs across teams
Improved testing, documentation and data quality practices for core models
Embedded yourself into agile delivery processes and cross-functional teams
Identified opportunities to improve scalability, clarity and reusability of data models
Requirements
Analytics Engineering Experience: Background in analytics engineering or a similar data modelling-focused role
SQL Expertise: Strong SQL skills with experience using cloud data platforms (e.g. Snowflake)
Data Modelling Skills: Proven ability to design scalable, well-structured and reusable data models
Tooling Experience: Experience with dbt, Python, Airflow or similar modern data stack tools
DataOps Practices: Familiarity with git, CI/CD and testing frameworks for data pipelines
Data Quality Focus: Strong understanding of validation, documentation and testing best practices
Stakeholder Collaboration: Ability to translate business needs into robust analytical datasets and definitions
Communication Skills: Able to explain technical concepts clearly to both technical and non-technical audiences
Mindset: Detail-oriented, pragmatic, proactive and comfortable working in fast-moving environments
Benefits
Vision insurance
Additional Information
Accepting applications until:
19 June 2026
Job Description
Your Role: Senior Analytics Engineer
A hands-on analytics engineering role focused on building trusted, scalable data models that power insight, measurement and AI-driven decision-making.
As a Senior Analytics Engineer at Global, you will:
Thisisglobal · Holborn - London