At a Glance
- Tasks: Build and maintain data pipelines, turning raw data into valuable insights.
- Company: Join a global blue-chip company with a focus on data monetisation.
- Benefits: Competitive salary, 25% bonus, private healthcare, and extra holiday perks.
- Other info: Dynamic team environment with opportunities for rapid career growth.
- Why this job: Make a real impact by working with rich customer data and innovative technologies.
- Qualifications: Solid Python and SQL skills, plus experience in data engineering and Google Cloud.
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. Nothing exotic, but you need to be comfortable working in an agile environment.
- 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) employer: Trades Workforce Solutions
Join a leading global blue chip company as a Data Engineer, where you'll be part of a dynamic team transforming rich customer data into impactful commercial products. With a strong focus on innovation, you'll enjoy a collaborative work culture that encourages growth and learning, alongside competitive benefits including private healthcare, generous annual leave, and a supportive pension scheme. Located in London, this role offers the unique opportunity to work with cutting-edge technology in a vibrant city, making it an excellent choice for those seeking meaningful and rewarding employment.
Contact Details:
Trades Workforce Solutions Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (External Data Products)
✨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 pipelines, SQL queries, and any projects you've worked on. This gives potential employers a taste of what you can do beyond just a CV.
✨Tip Number 3
Prepare for those interviews! Brush up on your Python and SQL skills, and be ready to discuss your experience with Google Cloud. Practice common data engineering scenarios to show you're the real deal.
✨Tip Number 4
Don't forget to apply through our website! It’s the quickest way to get your application seen by the right people. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Data Engineer (External Data Products)
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.
Keep It Clear and Concise:When writing your application, clarity is key! Use straightforward language and structure your thoughts well. Remember, we’re looking for code that’s not just functional but also easy for the next person to understand.
Demonstrate Your Learning Mindset:We love candidates who are eager to learn! Share any experiences where you’ve adapted to new technologies or tackled challenges in the fast-paced data landscape. Show us you’re ready to grow with us!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way to ensure your application gets into the right hands quickly. Plus, we’ll be in touch within 48 hours if you catch our eye!
How to prepare for a job interview at Trades Workforce Solutions
✨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, so you can confidently discuss your hands-on experience during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples of how you've built data pipelines and tackled data analysis challenges. Highlight any instances where you’ve improved existing processes or resolved quality issues, as this will demonstrate your ability to contribute meaningfully to the team.
✨Familiarise Yourself with Agile Practices
Since the role involves working in an agile environment, be ready to talk about your experience with tools like Jira and Confluence. Share how you’ve taken ownership of your tasks and participated in agile ceremonies, as this shows you’re a team player who can deliver on time.
✨Emphasise Your Willingness to Learn
The data landscape is always evolving, so express your genuine interest in continuous learning. Discuss any recent courses or projects that showcase your commitment to staying updated with industry trends, especially in machine learning and big data.
