Data Engineer — Enterprise Data & Lakehouse Platforms

Burberry; City Of London; On-site; GBP 65,000 - 90,000; Full time

Job summary

Burberry in City of London is seeking a Data Engineer to own data products underpinning reporting and analytics. You will work within cross-functional squads alongside Data Product Managers, Data Platform Engineers, and Visualisation & Reporting teams to deliver governed data products.

The role focuses on designing data models, transforming ingested data, and ensuring enterprise standards, with hands-on use of Databricks and lakehouse architectures.

Qualifications

• Experience in a data engineering role with cloud-based platforms.
• Proficiency in Python, SQL and Spark for ETL/ELT and modeling.
• CI/CD pipelines development and automation experience.
• Knowledge of metadata, data governance and business glossary alignment.
• Experience with lakehouse architectures and Delta/Parquet formats.

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 is consumable to 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), applying business logic to create clean, reusable products.
• Provide governed data products to the Visualisation & Reporting team, ensuring alignment with enterprise data definitions and the 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 - ensuring clean handoffs to Visualisation & Reporting Engineers.
• Support the productionisation of data science outputs where required, taking models or analyses developed in the business and engineering them into scalable, governed data products.
• Support L2/L3 data pipeline incidents where required, investigating and resolving data quality or pipeline failure issues in collaboration with the Data Platform Engineer (for infrastructure-level issues).
• Contribute to the 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 so downstream teams have stable and predictable consumption points.
• Embed privacy, PII handling, retention and access-control requirements into transformation logic in line with Data Governance, Cyber Security and platform guardrails.
• Support master and reference data handling, slowly changing dimensions and reusable dimensional/medallion modelling patterns where required by enterprise data products.

Skills

Python

SQL

Spark

Data modelling

CI/CD pipelines

Data governance

Cross-functional collaboration

Tools

Databricks

Delta Lake

Parquet

Job description

Burberry in City of London is seeking a Data Engineer to own data products underpinning reporting and analytics. You will work within cross-functional squads alongside Data Product Managers, Data Platform Engineers, and Visualisation & Reporting teams to deliver governed data products.

The role focuses on designing data models, transforming ingested data, and ensuring enterprise standards, with hands-on use of Databricks and lakehouse architectures.