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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Engineer - **Company:** Gymshark - **Location:** Solihull, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Airflow, BigQuery, Cloud Storage, Software Quality, Code Review, Continuous Integration, Information Engineering, Data Governance, Data Vault Modeling, Dimensional Modeling, Data Flow Control, Python (Programming Language), SQL Databases, Data Streaming, Google Cloud, Technical Debt, Data Strategy, Git, Data Analytics, Data Management, Terraform, Data Pipelines - **Published:** August 7, 2026 - **Apply:** https://eu.experteer.com/career/view-jobs/lead-data-engineer-solihull-grossbritannien-58832233 ## About the Role (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 Key requirements * Performance-based Bonus * Funded Healthcare * 25 days holiday + birthday+ bank holidays * Pension scheme * Flexible benefits (EV scheme, dental, cycle to work) * Employee Discount ## Description Experteer Overview 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. Pay / Benefits * 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 Tasks * 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 Key requirements * Performance-based Bonus * Funded Healthcare * 25 days holiday + birthday+ bank holidays * Pension scheme * Flexible benefits (EV scheme, dental, cycle to work) * Employee Discount ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Making Data Warehouses fast. 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