Lead Data Engineer

Salary: £54,000 - 57,000 per year

Requirements:

• Strong experience in data engineering in a senior or lead-level technical role.
• Deep expertise in Google Cloud Platform: BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Cloud Composer (Airflow) as the primary data platform stack.
• Advanced Python and SQL skills, including writing performant, production-grade code and conducting rigorous code reviews.
• Proven experience designing and building complex, scalable data pipelines using both batch and streaming/event-driven patterns.
• Strong data modelling skills: dimensional modelling, data vault, or equivalent, with a track record of building well-structured, reusable BigQuery data models.
• Experience with Dataform (or equivalent SQL-based transformation tools) for orchestrating transformations within BigQuery at scale.
• Solid understanding of software engineering principles: CI/CD, version control (Git), testing frameworks, and infrastructure as code (Terraform).
• Demonstrated ability to embed data quality, observability, and alerting into pipelines (automated validation, anomaly detection, monitoring).
• Experience leading technical design sessions, owning architecture decisions, and communicating trade-offs clearly to both technical and non-technical audiences.
• Track record of mentoring or coaching engineers and growing technical capability within a team.
• Strong cross-functional collaboration and stakeholder management skills, with experience translating business requirements into technical solutions.
• Experience with DataProc (Spark) for large-scale distributed data processing workloads.
• Familiarity with Looker or similar BI tooling, and an understanding of how data models feed downstream analytics and reporting.
• Exposure to analytics engineering practices and tooling (e.g. dbt conceptual patterns, data contracts, semantic layers).
• Experience in e-commerce or retail data environments is desirable.
• Familiarity with data mesh or data platform architecture patterns and their practical application in a scaled organisation.
• Experience with GCP cost management and BigQuery cost optimisation strategies.
• Broader exposure to ML infrastructure, feature engineering pipelines, or data science platform enablement.

Responsibilities:

• Own and drive the technical design and architecture of data pipelines, data models, and platform components across our team.
• Set and enforce engineering standards including code quality, testing, observability, security, and documentation.
• Lead technical discovery, design sessions, and code reviews, providing constructive, actionable feedback.
• Identify and drive resolution of technical debt, proactively surfacing risks and proposing pragmatic solutions.
• Evaluate emerging tools and technologies within the GCP ecosystem and beyond, and make grounded recommendations to the Data Engineering Manager.
• Work with the Data Engineering Manager to solve complex or ambiguous data engineering problems, unblocking our team and stakeholders.
• Ensure architectural decisions align with our data strategy, platform vision, and evolving business needs.
• Champion a culture of engineering excellence through example, documentation, and knowledge sharing.
• Mentor and coach Data Engineers from Junior through Senior level, supporting technical growth and career progression.
• Facilitate knowledge-sharing sessions, pairing, and documentation to build collective capability and reduce knowledge silos.
• Contribute to hiring by leading technical interviews, calibrating assessments, and helping onboard new team members effectively.
• Partner with the Data Engineering Manager on team development planning, identifying skill gaps and proposing learning opportunities.
• Partner with Data Governance to embed data quality, access control, and privacy by design into our engineering work.
• Collaborate cross-functionally with Data Product and wider Tech teams to ensure joined-up platform delivery.
• Maintain accurate and comprehensive technical documentation, including architecture decision records, runbooks, pipeline specs, and data dictionaries.
• Uphold data governance, security, and compliance standards across all data engineering activities.

Technologies:

• Airflow
• BigQuery
• CI/CD
• Cloud
• Composer
• Data Vault
• GCP
• Git
• Support
• Looker
• Python
• SQL
• Security
• Spark
• Terraform
• dbt

More:

We are Gymshark, a rapidly growing global team focused on uniting the conditioning community and giving people the tools they need to go further, faster, and stronger. This is a hybrid Lead Data Engineer role based in GSIQ, Solihull, UK, requiring attendance at least 3 days a week. We offer standard benefits including performance-based bonus opportunity, funded healthcare, 25 days holiday plus your birthday and bank holidays, pension, flexible benefits, Gymshark discount, wellbeing support, enhanced family leave, and life assurance, along with office-specific perks such as gym membership to The Lifting Club, onsite lunch provision and coffee bars, and EV charge points. We are an equal opportunities employer committed to inclusion and reasonable adjustments during recruitment.

last updated 36 week of 2026