Senior Data Engineer (GCP, BigQuery, Looker), PK [AS233]

About Smart Working
At Smart Working, we believe your job should not only look right on paper but also feel right every day. This isn’t just another remote opportunity - it’s about finding where you truly belong, no matter where you are. From day one, you’re welcomed into a genuine community that values your growth and well-being.

Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where you’re empowered to grow personally and professionally.

Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world.

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 tooling or process improvements where appropriate.

Requirements

• 5+ years of experience in SQL and data modelling, with strong command of dimensional modelling, star schemas, and performance optimisation.
• 3+ years working with Google BigQuery in a production environment.
• 3+ years hands-on experience with Google Cloud Platform (Cloud Storage, Dataflow, Pub/Sub, Cloud Functions, Composer).
• 3+ years building and maintaining ETL/ELT pipelines at scale.
• 1+ year working with Looker and LookML to deliver business-facing dashboards and data products.
• Demonstrable experience leading at least one data project end-to-end, from scoping through to delivery.
• Able to communicate clearly with non-technical stakeholders about data limitations, timelines, and trade-offs.
• Comfortable making pragmatic architecture decisions in a cloud-native, modern data stack environment.

Nice to Have

• Experience with dbt (Data Build Tool) for transformation layer management and testing.
• Familiarity with orchestration tools such as Apache Airflow or Cloud Composer.
• Python skills for pipeline scripting, data validation, or automation.
• Background in retail, ecommerce, or fashion, understanding how data flows across commercial and digital channels.
• Exposure to real-time or streaming data pipelines using Pub/Sub or Dataflow.
• Experience with Terraform or Infrastructure-as-Code practices in a GCP context.
• Familiarity with data governance frameworks, cataloguing, and lineage tracking.