Lead Data Engineer

As Lead Data Engineer at Gymshark, you will shape and deliver scalable data platforms while guiding the team to engineering excellence. You will own the technical design of data pipelines and models, ensure standards, and mentor engineers to raise capability. You will collaborate with data governance, product, and wider tech teams to align with the data strategy and platform vision. This role offers hands-on leadership in a fast-growing, data-driven business with a strong emphasis on quality, observability, and collaboration.

• Performance-based Bonus
• Funded Healthcare
• 25 days holiday + birthday+ bank holidays
• Pension scheme
• Flexible benefits (EV scheme, dental, cycle to work)
• Employee Discount

• Own and drive the technical design and architecture of data pipelines, data models, and platform components across the team
• Set and enforce engineering standards: code quality, testing, observability, security, and documentation
• Lead technical discovery, design sessions, and code reviews with actionable feedback
• Identify and resolve technical debt and surface risks with pragmatic solutions
• Evaluate emerging tools and technologies within the GCP ecosystem and beyond
• Collaborate with Data Engineering Manager to unblock complex data engineering problems
• Ensure architectural decisions align with Gymshark's data strategy and platform vision
• Champion engineering excellence through example, documentation, and knowledge sharing
• Mentor and coach Data Engineers across levels
• Facilitate knowledge sharing, pairing, and documentation to reduce silos
• Contribute to hiring through technical interviews and onboarding
• Partner on team development planning and upskilling
• Maintain comprehensive technical documentation and uphold governance standards

• Strong experience in data engineering at senior or lead level
• Deep expertise in Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer)
• Advanced Python and SQL with production-grade coding and code reviews
• Experience designing/building complex scalable data pipelines (batch and streaming)
• Strong data modelling skills (dimensional modelling, data vault) with reusable BigQuery models
• Experience with Dataform (or equivalent) for orchestrating BigQuery transformations
• Solid understanding of CI/CD, Git, testing, and Terraform
• Ability to embed data quality, observability, and alerting in pipelines
• Experience leading design sessions and communicating trade-offs to technical and non-technical audiences
• Mentoring or coaching experience and cross-functional collaboration skills

• Mentoring and coaching
• Cross-functional collaboration
• Strong communication and stakeholder management
• Data pipelines design (batch/streaming)
• GCP stack proficiency (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer)
• Python and SQL proficiency