We are looking for a "full-stack" Data Engineer to build the backbone of our data infrastructure and own the end-to-end data lifecycle. You will architect enterprise-grade systems and build products that drive digitalisation, while tackling high-volume challenges such as processing half-hourly meter reads for our energy customers.
Your responsibilities will include:
- Pipeline Architecture: Design, build, and maintain robust ETL/ELT pipelines to ingest large-scale datasets and high-frequency streams.
- Enterprise Warehousing: Lead the design and evolution of our enterprise data warehouse, ensuring it is scalable and performant.
- Modern Transformation: Manage our data transformation layer using Dataform (preferred) or dbt to orchestrate complex, reliable workflows.
- Quality & Deployment: Implement automated testing frameworks and deploy scalable services using Docker and Kubernetes to ensure operational health.
- Stakeholder Partnership: Act as a strategic partner to Product and Engineering, facilitating data design sessions to optimise how data is ingested and utilised.
- Mentorship & Standards: Raise the bar for technical excellence within the squad through code reviews, design sessions, and documenting best practices.
We put people first. It’s all about you..
- You have extensive experience leading the design of data systems and models.
- You are an expert in SQL and Python, with a proven ability to independently implement complex, production-ready projects.
- You possess a deep understanding of dimensional modelling (Kimball) or Data Vault methodologies, essential for creating scalable enterprise schemas.
- You have a track record of leading high-impact initiatives that align with company strategy. You can evaluate proposed work against team goals and provide critical feedback to ensure value delivery.
- You are capable of driving the end-to-end delivery of large-scale features, providing high-quality architectural diagrams and technical documentation.
- You have strong experience with modern DevOps practices, including Infrastructure as Code, GitOps, and managing transformation layers at scale.
- You can advise senior stakeholders on applying Data Engineering to solve complex business problems and are comfortable facilitating cross-functional design sessions.
- You role-model UW values by promoting a data-driven culture, mentoring peers, and communicating technical successes and failures clearly to the wider Technology & Product department.
Skills / Competencies
- Strategic Problem Solving: Ability to break down vague, high-level business requirements into concrete, scalable technical architectures.
- Clear Communication: Excellent verbal and written skills, with the ability to influence technical and non-technical audiences.
- Accountability: Willi