Senior Analytics Engineer
Global
- Holborn, England, United Kingdom
- Holborn, England, United Kingdom
À propos
Accepting applications until:
1 May 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: Key Responsibilities
•
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 What You'll Need
•
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 ]]>
Compétences linguistiques
- English
Avis aux utilisateurs
Cette offre provient d’une plateforme partenaire de TieTalent. Cliquez sur « Postuler maintenant » pour soumettre votre candidature directement sur leur site.