At a Glance
- Tasks: Build and maintain impactful data pipelines and create valuable customer insights.
- Company: Join a global blue-chip company with rich customer data.
- Benefits: Competitive salary, 25% bonus, private healthcare, and extra holiday perks.
- Other info: Dynamic agile environment with opportunities for rapid career growth.
- Why this job: Make a real difference by transforming raw data into high-value products.
- Qualifications: Solid Python and SQL skills, plus hands-on data engineering experience.
The predicted salary is between 46000 - 69000 € per year.
Global Blue Chip £46k - £69k base + 25% bonus + company benefits (10% match pension, 25 days annual leave plus your birthday off, private healthcare + more) London - 2 days a week.
Most data engineering jobs are about keeping the lights on. This one is about building something that actually matters. Our client is sitting on some of the richest customer data in the UK. The team you'd be joining turns that raw data into high-value customer signals and commercial data products - the kind of work that has real commercial weight behind it.
As a Data Engineer, you won't be babysitting old pipelines. You'll be building new ones, writing clean Python and SQL, working with ML models to find genuine customer insights, and contributing to a platform built on Google Cloud.
What you'll be doing:
- Building and maintaining data pipelines and warehousing solutions that actually hold up under pressure.
- Writing code that follows proper governance and quality standards — not just code that works, but code the next person can understand and build on.
- Using analytical and modelling techniques across a vast dataset to create customer insights and segments that have real commercial value.
- Collaborating with internal teams to understand what data is available, hunt down quality issues, and make sure the products you're contributing to are reliable.
- Taking ownership of your tickets, showing up to agile ceremonies, and shipping work on time.
What you need to bring:
- Solid Python and SQL. This is non-negotiable.
- Real experience as a Data Engineer, building pipelines and doing data analysis — not just exposure to it.
- Hands-on experience with Google Cloud, specifically BigQuery, Cloud Run and DBT Cloud.
- Version control and CI/CD experience, ideally with GitLab.
- Familiarity with Jira and Confluence.
- A genuine willingness to learn. The data landscape moves fast. If you need everything pinned down before you start, this probably isn't the right fit.
Nice to have:
- Some experience with machine learning, specifically BigQueryML, MLOps or Gen AI applications.
- Experience working with big data at scale.
The benefits:
- Bupa healthcare from day one.
- Income protection if you're unable to work.
- Life assurance.
- A birthday day off.
- Option to buy or sell up to 5 days' holiday.
- Discounts on our clients' products for you and your family.
- Plus a pension with employer contributions.
Next steps:
Two-stage interview process if shortlisted. This role will move quickly. If it's caught your attention, don't sit on it. Apply now, and one of our team will be in touch within 48 hours.
Data Engineer (External Data Products) in London employer: Edge Tech
Join a leading global blue chip company as a Data Engineer, where you'll have the opportunity to work with some of the richest customer data in the UK. With a strong focus on innovation and collaboration, our work culture encourages personal growth and offers extensive benefits including private healthcare, generous annual leave, and a supportive environment for professional development. Located in London, this role not only provides a competitive salary and bonus structure but also allows you to contribute to meaningful projects that drive real commercial value.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (External Data Products) 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 engineering projects, especially those involving Python, SQL, and Google Cloud. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and coding challenges. Practice makes perfect, so consider mock interviews with friends or using online platforms.
✨Tip Number 4
Don't forget to apply through our website! It’s the quickest way to get noticed. Plus, we love seeing candidates who take the initiative to reach out directly.
We think you need these skills to ace Data Engineer (External Data Products) in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your solid Python and SQL skills in your application. We want to see real experience, so don’t just mention it—give examples of how you've built pipelines and done data analysis.
Tailor Your Application:Take a moment to tailor your application to the job description. Mention your hands-on experience with Google Cloud and any relevant tools like BigQuery or DBT Cloud. This shows us you’ve done your homework!
Be Yourself:Let your personality shine through! We’re looking for someone who’s genuinely willing to learn and adapt. Share a bit about your journey and what excites you about working in data engineering.
Apply Through Our Website:Don’t forget to apply through our website! It’s the quickest way for us to get your application and start the conversation. Plus, we’ll be in touch within 48 hours if you catch our eye!
How to prepare for a job interview at Edge Tech
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and SQL, as these are non-negotiable for the role. Brush up on your Google Cloud knowledge, especially BigQuery, Cloud Run, and DBT Cloud. Being able to discuss your hands-on experience with these technologies will show that you're not just familiar but truly capable.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've built data pipelines or solved complex data issues. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will help you demonstrate your analytical skills and how you can contribute to creating valuable customer insights.
✨Emphasise Collaboration
Since the role involves working closely with internal teams, be ready to talk about your experience in collaborative environments. Share instances where you’ve worked with others to tackle quality issues or improve data reliability. This shows you’re a team player who values communication and teamwork.
✨Demonstrate Your Willingness to Learn
The data landscape is always evolving, so express your eagerness to learn new tools and techniques. Mention any recent courses or projects you've undertaken to stay updated. This will highlight your adaptability and commitment to professional growth, which is crucial for this fast-paced role.
