Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build scalable data models and ensure data quality for impactful decision-making.
- Company: Join a forward-thinking company focused on AI-driven analytics.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Shape the future of analytics and make a real difference in business decisions.
- Qualifications: Experience in analytics engineering and strong SQL skills required.
The predicted salary is between 60000 - 80000 £ per year.
Accepting applications until: 19 June 2026
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
Senior Analytics Engineer in London employer: Global Media Group
Contact Detail:
Global Media Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Analytics Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data models and projects. This is your chance to demonstrate your SQL expertise and data modelling skills in action, making you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical teams.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Senior Analytics Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Analytics Engineer role. Highlight your analytics engineering experience, SQL expertise, and any relevant tools you've used. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about analytics engineering and how your background makes you a perfect fit for us. Don’t forget to mention specific projects or achievements that showcase your skills.
Showcase Your Data Modelling Skills: Since this role focuses heavily on data modelling, be sure to include examples of scalable and reusable data models you've designed. We love seeing how you've turned complex data into clear insights, so share those success stories!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Global Media Group
✨Know Your Data Models
Make sure you brush up on your data modelling skills before the interview. Be ready to discuss how you've designed and maintained scalable data models in the past, and think of specific examples that showcase your expertise in SQL and cloud data platforms like Snowflake.
✨Showcase Your Testing Frameworks
Prepare to talk about your experience with data quality and testing. Highlight any robust testing frameworks you've implemented and how they improved data accuracy. This will demonstrate your commitment to maintaining high standards in data reliability.
✨Collaborate Like a Pro
Since this role involves working closely with various teams, be ready to share examples of how you've successfully collaborated with analytics, product, and data science teams. Discuss how you’ve translated complex business needs into actionable datasets and metrics.
✨Communicate Clearly
Practice explaining technical concepts in simple terms. You might encounter non-technical stakeholders during the interview, so being able to convey your ideas clearly will show that you can bridge the gap between technical and non-technical audiences effectively.