Senior Data Engineer

We are looking for an experienced Senior Data Engineer to help design, build, and evolve our modern data platform. You will shape our data warehousing, data products, and self service analytics, ensuring our data is trusted, well governed, and AI ready, working closely with the Head of Data & AI and the wider Data & AI team.‑service analytics‑governed, and AI‑ready

This is a hands on senior individual contributor role with clear technical leadership expectations. You will own complex data domains and pipelines, set and uphold engineering standards, and mentor other data engineers, while still spending a significant portion of your time building.‑on senior individual contributor role with clear technical leadership expectations. You will own complex data domains and pipelines, set and uphold engineering standards, and mentor other data engineers, while still spending a significant portion of your time building.

Key Responsibilities:

Design & Evolve Scalable Data Warehousing Solutions:

• Lead the design, build, and maintenance of robust, well tested ELT / ETL pipelines and transformation workflows‑tested ELT / ETL pipelines and transformation workflows
• Model and maintain curated data layers to support reporting, analytics, and operational decision making‑making
• Optimise the performance, reliability, and cost of our cloud data warehouse
• Contribute to data architecture decisions, patterns, and standards in partnership with the Head of Data & AI

Enable Data Democratisation & Self Service‑Service:

• Design intuitive, well structured data models that power self serve BI (e.g. AWS QuickSight, SQL export)‑structured data models that power self‑serve BI (e.g. AWS
• Partner with analysts and domain teams to make data products genuinely usable and widely adopted
• Contribute to data enablement initiatives such as training sessions, playbooks, and internal documentation
• Help develop and maintain data dictionaries, business glossaries, and technical catalogues

 Governance, Quality, and Compliance by Design:

• Embed data quality checks, alerts, observability, and access controls into pipelines and data products from the outset
• Support data governance capabilities (classification, lineage, audit, retention) using automated tooling where possible
• Work closely with risk, security, and compliance stakeholders to ensure adherence to internal and external requirements (e.g. GDPR)
• Ensure our core data assets are AI ready by enforcing high standards for data quality, provenance, and documentation, so they can safely power analytics, machine learning, and future AI use cases‑ready

Technical Leadership & Collaboration:

• Provide technical guidance and code review for other data engineers, helping to raise the bar on quality and reliability
• Contribute to shared engineering practices (coding standards, testing strategy, CI/CD, observability)
• Collaborate in an agile environment with product, analysts, and stakeholders to break down work and deliver iteratively
• Help evaluate and introduce new tools, patterns, and approaches to improve o