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- Tasks: Build and optimise scalable data pipelines and create clean datasets for AI and analytics.
- Company: Join Checkatrade, the UK's leading home improvement marketplace, in an exciting AI era.
- Benefits: Enjoy competitive salary, bonuses, health support, gym membership, and flexible holiday options.
- Other info: Collaborative environment with opportunities to learn and grow alongside talented teams.
- Why this job: Make a real impact by shaping data foundations that power smarter customer journeys.
- Qualifications: Solid Python and SQL skills, experience with AWS, and a passion for data quality.
The predicted salary is between 50000 - 60000 £ per year.
Important: visa sponsorship is not available for this role. 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.
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.
Skills & 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 a 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!
How we'll get to know each other:
- Screening call with one of our Talent Acquisition Partners
- Technical interview with the VP Data
- Third stage interview with the Data team
Data Engineer employer: Checkatrade
Contact Detail:
Checkatrade Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. We all know that sometimes it's not just what you know, but who you know that can help you land that Data Engineer role.
✨Tip Number 2
Prepare for those technical interviews! Brush up on your Python and SQL skills, and be ready to discuss your experience with AWS and data pipelines. We want to see how you think through problems, so practice explaining your thought process.
✨Tip Number 3
Show off your projects! If you've built any data pipelines or worked on relevant projects, make sure to highlight them during interviews. We love seeing practical examples of your skills in action.
✨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 us you're genuinely interested in joining our team at Checkatrade.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Python, SQL, and AWS, and don’t forget to mention any relevant projects that showcase your skills in building scalable pipelines and data models.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how your background aligns with our mission at Checkatrade. Be sure to mention your eagerness to learn new tools and technologies.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled challenges in data quality or performance optimisation. We love seeing candidates who can think critically and come up with innovative solutions!
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!
How to prepare for a job interview at Checkatrade
✨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 past projects. This will show that you have a solid foundation and can handle the technical challenges of the role.
✨Familiarise Yourself with AWS Tools
Since the role involves working with AWS and modern data stack tools, make sure you understand the basics of S3, Airflow, and other relevant technologies. If you haven't used them yet, do some quick research or tutorials to get a grasp of their functionalities.
✨Communicate Clearly and Collaboratively
Prepare to demonstrate your ability to work across teams. Think of examples where you've translated complex data needs into actionable tasks for Analysts or Data Scientists. Clear communication is key, so practice explaining your thought process in simple terms.
✨Show Your Passion for Data Quality
Express your commitment to data quality and performance optimisation during the interview. Share specific instances where you implemented monitoring or quality checks in your previous roles. This will highlight your dedication to ensuring reliable data for downstream users.