Burberry Data Engineer
- Employment
- Full-Time
- Seniority
- Mid-Level
- Department
- IT & Technology Systems
- Industry
- Fashion, Apparel & Leather Goods
- Posted
- Jul 23, 2026
About Burberry
Burberry Limited, a quintessentially British luxury fashion house, is renowned for its innovative designs and commitment to quality. As part of the global luxury conglomerate, Burberry offers a dynamic and inclusive work environment where creativity and excellence are at the forefront. The company is dedicated to fostering a culture that encourages diversity and sustainability, making it a leader in the luxury industry.
Burberry seeks a Data Engineer in London to design data models, manage transformation layers, and ensure data governance across enterprise platforms. Python, SQL, Spark, Databricks required.
Role & Responsibilities
- Design and build data models and transformation logic to turn ingested data into governed products across domains such as Customer, Product, Order, Sale, and Supply Chain
- Manage the engineering layer between platform-level ingestion and reporting/visualisation output to ensure data meets enterprise standards
- Collaborate with Data and Solution Architects to ensure work aligns with enterprise data models and platform strategy
- Work with Data Platform Engineers to consume data from the enterprise platform (Databricks) and apply business logic to create clean, reusable products
- Provide governed data products to the Visualisation & Reporting team, ensuring alignment with enterprise data definitions and business glossary
- Embed quality controls, validation, testing, and monitoring into the transformation layer by design
- Maintain clear documentation of business rules, data lineage, and transformation logic to support team-wide consistency
- Facilitate the shift from third-party-led to internal ownership by participating in knowledge transfer and establishing in-house engineering standards
- Function within a squad-based delivery model, dynamically allocated to cross-functional squads based on prioritised demand
- Work with Data Product Managers to understand business requirements and translate them into technically sound data engineering outputs
- Define and maintain interface contracts between data engineering outputs and the reporting/visualisation layer
- Support productionisation of data science outputs, taking models or analyses and engineering them into scalable, governed data products
- Support L2/L3 data pipeline incidents, investigating and resolving data quality or pipeline failure issues
- Contribute to continuous improvement of data engineering practices, reusable patterns, and team knowledge
- Apply consistent engineering practices including Git branching, peer review, reusable components, automated testing, CI/CD quality gates and clear code ownership
- Define and maintain data contracts, data product versioning and semantic-readiness requirements
- Embed privacy, PII handling, retention and access-control requirements into transformation logic
- Support master and reference data handling, slowly changing dimensions and reusable dimensional/medallion modelling patterns
Qualifications
- Experience in a data engineering role building models and transformation layers in a modern, cloud-based environment (e.g., Databricks)
- Proficiency in Python, SQL, and Spark, with practical experience in ETL/ELT processes and data modelling
- Experience developing and working with CI/CD pipelines
- Experience developing and applying metadata-driven data ingestion frameworks
- Solid understanding of dimensional/relational modelling, data quality management, and integration patterns
- Familiarity with data governance principles, metadata standards, and business glossary alignment
- Proven ability to work effectively within cross-functional squads and alongside third-party resources
- Strong software engineering discipline, including source control, peer review, unit/integration testing, deployment automation and production support practices
Skills
Experience
Proven experience in a data engineering role building data models and transformation layers in a modern, cloud-based environment. Practical background with ETL/ELT processes, metadata-driven ingestion frameworks, and dimensional/relational modelling patterns. Demonstrated expertise working within cross-functional teams and transitioning from outsourced delivery models is beneficial. Understanding of data quality principles, privacy, and access control requirements for enterprise data products.
Workplace
This position is based in London, England, UK.
Culture
Burberry fosters a creative and inclusive workplace culture that values diversity and sustainability. The company is committed to being a force for good, driving industry change and championing community engagement.
About Cerulean
Cerulean is the definitive career portal for the global luxury industry. We match exceptional professionals with exclusive opportunities at the world's most prestigious brands. From haute couture and fine watchmaking to prestige beauty, hospitality, and boutique retail, Cerulean centralises luxury employment to help you find the career for which you were destined.
Frequently Asked Questions
The luxury industry is characterised by a diverse and nuanced nomenclature. Esteemed houses frequently employ proprietary terminology, and even within a single organisation like Burberry, titles may vary across global markets to reflect local conventions. To ensure absolute clarity, Cerulean assigns a standardised, industry-coherent canonical title to every listing. However, it is worth noting that this role is functionally synonymous with «Data Product Engineer», «Analytics Engineer», «Data Transformation Engineer», «Data Pipeline Engineer», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.