At a Glance
- Tasks: Build scalable data pipelines and optimise datasets for AI and machine learning.
- Company: Join Checkatrade, the UK's leading home improvement marketplace.
- Benefits: Competitive salary, bonuses, health support, gym membership, and more perks.
- Other info: Collaborative culture with opportunities for personal and professional growth.
- Why this job: Shape the future of AI in a dynamic, innovative environment.
- Qualifications: Solid Python and SQL skills; AWS experience is a plus.
The predicted salary is between 50000 - 60000 € per year.
As our next Data Engineer, you'll play a key role in helping us build the UK's go-to home improvement marketplace. You'll be at the heart of Checkatrade's AI era building the trusted, governed data foundations that power smarter customer journeys, better trade matching, and intelligent automation across the business. This isn't just about moving data from A to B; it's about creating the scalable pipelines, clean datasets, and robust platform capabilities that let AI and machine learning work safely and effectively in production.
Forget long lists, here's what you'll actually spend your time on:
- Building and optimising scalable ETL and ELT pipelines on AWS integrating data from internal and external systems and turning it into clean, reusable datasets ready for analytics, machine learning, and AI‑powered product experiences.
- Developing data models and feature‑ready datasets that support both human decision‑making and machine intelligence, including work that feeds directly into customer‑facing AI services.
- Defining and maintaining data SLAs, quality checks, and monitoring so our platform stays reliable, performant, and trustworthy and so the teams depending on it can crack on with confidence.
- Collaborating closely with Data Scientists, Analysts, Product teams, and Software Engineers to understand what high‑quality data looks like for each use case and deliver it in a way that’s governed, lineage‑tracked, and easy to work with.
- Contributing to platform observability, orchestration reliability, and access patterns that make AI safe in production clear lineage, robust pipelines, and repeatable processes from source to serving.
- Helping shape engineering standards and best practices across the data team from data modelling and transformation to performance optimisation and troubleshooting so the whole platform keeps getting better.
Qualifications
- Solid data engineering fundamentals – writing Python and SQL, building pipelines, modelling data, and knowing how to debug when things go wrong in production.
- Experience with AWS and modern data stack tools such as S3, Airflow, Trino, Iceberg, or NoSQL systems or the genuine eagerness to learn them quickly in a real production environment.
- A real care for data quality, monitoring, and performance optimisation, you want the data downstream to actually be right, not just the pipeline to run green.
- The ability to work across teams and communicate clearly, you can translate what an Analyst or Data Scientist needs into something well‑engineered, documented, and ready for scale.
Benefits
- Competitive salary + annual bonus or commission (role dependent)
- Employee Share Programme
- Health, well‑being and learning support
- Gym membership, Smart Tech Scheme and Cycle Scheme
- Birthday/Special day leave
- Buy & sell holiday scheme
- 1 week's paid charity leave and much more!
Data Engineer employer: View, Inc.
At Checkatrade, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Data Engineer, you'll not only contribute to building the UK's leading home improvement marketplace but also enjoy a range of benefits including competitive salaries, employee share programmes, and generous leave policies. Our commitment to employee growth is evident through our support for health, well-being, and continuous learning, making this an ideal place for those seeking meaningful and rewarding careers in data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even local tech events. The more people you know, the better your chances of landing that Data Engineer role at Checkatrade.
✨Show Off Your Skills
Create a portfolio showcasing your data engineering projects. Whether it's building pipelines or optimising datasets, having tangible examples of your work can really impress potential employers. Don't forget to share it on platforms like GitHub!
✨Ace the Interview
Prepare for technical interviews by brushing up on Python, SQL, and AWS tools. Practice common data engineering problems and be ready to discuss how you've tackled challenges in past projects. Confidence is key!
✨Apply Through Our Website
Make sure to apply directly through the Checkatrade website. It shows you're genuinely interested and gives you a better chance of being noticed. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your data engineering fundamentals, especially your experience with Python and SQL. We want to see how you've built pipelines and modelled data in the past, so don’t hold back on those details!
Tailor Your Application:Read through the job description carefully and tailor your application to match. Use the same language and keywords we’ve used to describe the role. This shows us you understand what we're looking for and that you're genuinely interested.
Demonstrate Your Passion for Data Quality:We care about data quality and performance optimisation, so share examples of how you've ensured data integrity in your previous roles. Let us know how you monitor and maintain high standards in your work!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at View, Inc.
✨Know Your Data Engineering Fundamentals
Brush up on your Python and SQL skills before the interview. Be ready to discuss how you've built pipelines and modelled data in the past. They’ll want to see that you can debug issues in production, so have some examples ready to share.
✨Familiarise Yourself with AWS and Tools
If you’re not already familiar with AWS and tools like S3, Airflow, or Trino, take some time to learn the basics. Even if you don’t have hands-on experience, showing genuine eagerness to learn these tools can set you apart from other candidates.
✨Emphasise Data Quality and Performance
Be prepared to talk about your approach to ensuring data quality and performance optimisation. Share specific instances where you implemented monitoring or quality checks to ensure reliable data downstream. This shows you care about more than just getting the pipeline to run.
✨Communicate Clearly Across Teams
Highlight your ability to collaborate with Data Scientists, Analysts, and Product teams. Prepare examples of how you’ve translated complex requirements into well-engineered solutions. Clear communication is key, so practice articulating your thoughts concisely.
