Data Engineer

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.

It's not about ticking every box. It's about turning up curious, ready to crack on. You'll do well here if you bring:

• 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.

• 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!