Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build scalable data infrastructure for AI-driven products and audience intelligence.
- Company: Join a leading global media company with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team culture with excellent career advancement opportunities.
- Why this job: Shape the future of data engineering and make a real impact in a collaborative environment.
- Qualifications: Strong Python and SQL skills, experience with modern data tools and cloud environments.
The predicted salary is between 50000 - 65000 £ per year.
Your role: Data Engineer
A hands-on role building scalable data infrastructure that powers AI-driven products and audience intelligence.
As a Data Engineer at Global, you will:
- Key Responsibilities
- Data Platform & Pipeline Engineering (60%): Design, build and maintain scalable batch and near real-time pipelines across ingestion, transformation and serving layers. Develop reusable data models and optimise performance, reliability and cost.
- Platform Evolution & Engineering Excellence (20%): Shape the Global:IQ data platform through best practices in architecture, tooling, CI/CD and infrastructure as code. Create reusable components and maintain clear technical documentation.
- Quality & Governance (10%): Implement robust data validation, testing, lineage and observability to ensure high-quality, trusted datasets. Support governance and privacy-conscious data handling.
- Collaboration & Enablement (10%): Partner with Data Science, MLOps, Product and commercial teams to deliver production-ready data solutions. Support and mentor others while communicating clearly with stakeholders.
What You’ll Love About This Role
- Think Big: Build a data platform from the ground up that will scale with a cutting-edge AI and ML product.
- Own It: Take responsibility for production-grade data systems that directly power targeting, optimisation and measurement.
- Keep it Simple: Apply pragmatic engineering to deliver reliable, maintainable solutions without over-engineering.
- Better Together: Work in a highly collaborative, cross-functional team spanning technical and commercial expertise.
What Success Looks Like
In your first few months, you’ll have:
- Developed a strong understanding of the Global:IQ platform and its core use cases
- Successfully onboarded key datasets with robust ingestion and quality standards
- Delivered reliable pipelines supporting live production use cases
- Established or improved data engineering standards and best practices
- Built strong working relationships across Data, Product and commercial teams
- Identified opportunities to improve scalability, reliability and efficiency
What You'll Need
- Programming & Data Skills: Strong Python and SQL skills, with experience building production-grade data pipelines
- Data Platform Experience: Hands-on experience with modern data tools (e.g. Snowflake, Airflow, dbt) and cloud environments (preferably AWS)
- Engineering Best Practice: Knowledge of CI/CD, testing, version control and infrastructure as code
- Data Quality & Governance: Understanding of observability, validation and maintaining reliable data systems
- Collaboration & Communication: Ability to translate business and data science needs into scalable solutions and communicate clearly with stakeholders
- Mindset & Approach: Pragmatic, ownership-driven and curious, with a passion for building impactful data products
Data 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 Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts. 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 projects, pipelines, and any cool stuff you've built. This is your chance to demonstrate your hands-on experience and make a lasting impression.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process and how you tackle challenges—this will help you stand out as a problem-solver.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from passionate candidates like you. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your Python and SQL expertise, as well as any hands-on experience with data tools like Snowflake or Airflow. We want to see how you can contribute to our data platform!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about building scalable data infrastructure and how your previous experiences align with our mission at StudySmarter. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on relevant projects, whether in a professional setting or as personal endeavours, make sure to include them. Describe the challenges you faced and how you overcame them, especially in terms of data pipeline engineering and quality governance. We appreciate real-world examples!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy and ensures your application goes straight to us. Plus, you’ll get to explore more about our culture and values while you’re at it!
How to prepare for a job interview at Global Media Group
✨Know Your Data Tools
Familiarise yourself with the modern data tools mentioned in the job description, like Snowflake, Airflow, and dbt. Be ready to discuss your hands-on experience with these tools and how you've used them to build scalable data pipelines.
✨Showcase Your Python and SQL Skills
Prepare to demonstrate your programming skills, especially in Python and SQL. Think of specific examples where you've built production-grade data pipelines and be ready to explain your thought process and the challenges you faced.
✨Understand CI/CD and Best Practices
Brush up on your knowledge of CI/CD, testing, and infrastructure as code. Be prepared to talk about how you've implemented these practices in previous roles and how they contribute to building reliable data systems.
✨Emphasise Collaboration
Since this role involves working closely with various teams, think of examples that highlight your collaboration skills. Be ready to discuss how you've partnered with Data Science or Product teams to deliver effective data solutions and how you communicate technical concepts to non-technical stakeholders.