Senior Data Engineer GCP, BigQuery, Looker - Smart Working

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About the Role We're looking for a Senior Data Engineer to become a cornerstone of our data platform team. This is a long-term, strategic role, not a short sprint. You'll be embedded in a collaborative engineering and analytics team, working across the full data lifecycle: ingestion, transformation, modelling, and surfacing insights through Looker. You'll work closely with stakeholders across commercial, product, and marketing to ensure data is reliable, scalable, and meaningful. You'll be given real ownership. This is a role for someone who wants to shape standards, improve the architecture, and grow with a brand that takes its data seriously.

Responsibilities

• Design, build, and maintain robust ETL/ELT pipelines that move data from source systems into Google BigQuery, ensuring reliability, scalability, and observability at every stage.
• Develop and enforce data models and schema standards using best-practice SQL and dimensional modelling principles, with a focus on clarity, reuse, and performance.
• Own the Google BigQuery environment, optimising queries, managing costs, enforcing data governance, and ensuring the platform scales alongside the business.
• Build and maintain Looker explores, LookML models, and dashboards that translate complex datasets into clear, actionable business intelligence for non-technical stakeholders.
• Work across the full Google Cloud Platform stack, including Cloud Storage, Dataflow, Pub/Sub, Cloud Functions, and Composer, to architect end-to-end data solutions.
• Partner with analytics, engineering, and commercial teams to understand data requirements and translate business problems into scalable technical solutions.
• Champion data quality and testing frameworks, implementing monitoring and alerting so that issues are caught early and resolved quickly.
• Contribute to documentation, coding standards, and architectural decision records so the team can move fast with confidence.
• Mentor junior data team members and set the bar for engineering rigour across the data function.
• Stay current with developments in the modern data stack and proactively recommend to