Junior Data Engineer

We are seeking a Junior Data Engineer to join our Digital Engineering, Digital & IT team in the UK, with flexible working across Newbury and Paddington.

Reporting to the Data Strategy & Engineering Lead, you will develop foundational production Data Engineering capability while contributing to trusted data products and platforms with appropriate technical guidance.

You will work with technologies including Python, SQL, dbt or equivalent transformation tools, cloud data services and version control, implementing well-defined data pipelines, transformations, automated tests and operational activities. You will also gain practical experience of AI-assisted engineering while maintaining clear human accountability for generated outputs, security, privacy, traceability and production quality.

What you’ll do

• Develop and test defined SQL, Python and dbt or equivalent transformation components using established engineering patterns.
• Support data ingestion, transformation and data-model changes with guidance from Lead and Senior Data Engineers.
• Implement agreed data-quality checks, documentation, metadata and lineage for assigned components.
• Use version control, pull requests, continuous delivery and automated testing consistently.
• Respond constructively to code-review feedback and apply learning to future engineering work.
• Monitor assigned data jobs and investigate straightforward failures.
• Maintain clear and useful operational runbooks and support effective operational handover.
• Escalate complex incidents, security issues or control concerns with relevant evidence.
• Follow agreed engineering, security, privacy and data-quality standards.
• Build technical capability through practical delivery, pairing, review and operational feedback.
• Use AI-assisted development tools responsibly, validating generated outputs before they are incorporated into engineering work.

Who you are

You are an early-career data professional looking to establish and develop practical Data Engineering expertise in a production technology environment.

You will bring:

• Foundational knowledge of Python and SQL.
• Working knowledge of relational data and core data-transformation principles.
• Early-career experience gained through employment, an apprenticeship, placement, graduate study or equivalent practical delivery.
• Exposure to cloud data services, preferably Google Cloud Platform or an equivalent cloud environment.
• An understanding of version control, automated testing, continuous delivery and code-review practices.
• Awareness of data quality, privacy, access controls and secure data handling.
• An interest in responsible AI-assisted development, including validation of AI-generated outputs.
• Clear written and verbal communication skills, including the ability to document technical work effectively.
• A willingness to seek support, learn through pairing and feedback, and contribute collaboratively to team outcomes.

What's in it for you

• The opportunity to develop practical Data Engineering capability by contributing to production data products and platforms.
• Exposure to cloud-native engineering, reusable data capabilities and digital services supporting customer propositions and operational use cases.
• Structured learning through pairing, technical review, delivery and operational feedback.
• Experience working with established engineering practices covering automated testing, continuous delivery, data quality, security, metadata and lineage.
• The opportunity to build increasing independence as your technical capability develops.
• Practical exposure to the responsible use of AI-assisted engineering tools within a production environment.
• Flexible UK working across Newbury and Paddington.

What skills you will learn

Through this role, you will have opportunities to develop your capabilities in:

• Production Python and SQL development.
• Data ingestion, transformation and modelling.
• dbt or equivalent data-transformation practices.
• Cloud data engineering, including exposure to Google Cloud Platform or equivalent services.
• Automated testing and data-quality controls.
• Version control, pull requests and collaborative code review.
• Continuous-delivery practices for data engineering.
• Metadata, documentation and data lineage.
• Production monitoring, troubleshooting, runbooks and incident escalation.
• Secure and privacy-aware handling of data.
• Responsible AI-assisted software and data engineering, including validation of generated outputs.