Data Engineer

Mulberry England

. Design and document the target data platform architecture with the Head of Data .

Posted 11/11/2026full-timeLondon • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building cloud-based data platforms, particularly utilizing Google Cloud Platform and BigQuery. Proficient in developing ETL and ELT pipelines, ensuring data quality, and implementing governance requirements across diverse data environments.

Highest-signal resume keywords

Google Cloud PlatformBigQueryETL and ELT TechniquesData ArchitectureSQL

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModellingIntegration ArchitectureData WarehousingData Quality ControlsData LineageMetadata ManagementAnalytical SkillsProblem-SolvingTroubleshootingTechnical Design

Soft Skills

Clear CommunicationStakeholder ManagementIndependent WorkLeadershipAdaptability

Tools & Technologies

DbtData Transformation ToolsAnalytics PlatformsMachine LearningArtificial Intelligence

Certifications & Qualifications

Google Cloud CertificationData Engineering Certification

Industry Keywords

RetailConsumerLuxuryFashionEcommerceOmnichannel

Tech Stack

Tools & technologies

BigQueryCloudERPETLGoogle Cloud PlatformSQL

About the role

Key responsibilities & impact

Design and document the target data platform architecture with the Head of Data
Develop engineering principles, integration patterns, data models and technical standards
Assess source-system, platform and service integrations to create a scalable data architecture
Identify architectural risks, technical debt and dependencies and recommend solutions
Design, build, test and maintain ETL and ELT pipelines across core business systems and third-party data sources
Develop and optimise data structures, datasets and transformation processes in Google Cloud Platform and BigQuery
Create reusable integration components and engineering patterns
Monitor, document and support data pipelines throughout their lifecycle
Investigate and resolve complex data, integration and platform issues
Design logical and physical data models for reporting, analytics and operational use cases
Build a semantic layer for self-service reporting and an MCP layer for natural-language interrogation
Implement data quality controls, validation and monitoring
Enable data lineage, metadata and auditability across priority data domains
Establish data definitions, ownership and appropriate access with data owners and stakeholders
Ensure compliance with data protection, retention, security and regulatory requirements
Translate business and architectural requirements into technical designs and engineering solutions
Collaborate with Technology teams, business stakeholders and specialist partners
Provide technical guidance, review third-party designs and code
Produce architecture diagrams, data flows, mappings, standards and support documentation
Support knowledge transfer and capability development across internal Technology teams
Help shape the data platform roadmap
Support planned releases or critical data platform issues outside normal working hours when required
Promote Mulberry’s values, inclusive culture and sustainability strategy

Requirements

What you’ll need

Significant experience designing and building modern cloud-based data platforms
Strong hands-on experience with Google Cloud Platform, particularly BigQuery and associated data services
Proven experience designing, developing and supporting enterprise data pipelines using ETL and ELT techniques
Strong SQL capability and experience working with structured and semi-structured data
Experience in data architecture, data modelling, integration architecture and data warehousing
Experience integrating data from multiple enterprise and third-party source systems
Experience implementing data quality controls, lineage, metadata and governance requirements within technical solutions
Ability to turn incomplete or inconsistent information into clear technical designs and delivery priorities
Strong analytical, problem-solving and troubleshooting skills
Clear communication and stakeholder management skills, including explaining technical concepts to technical and non-technical audiences
Ability to work independently, lead technical workstreams and deliver high-quality outputs in a changing environment
Experience within retail, consumer, luxury, fashion, ecommerce or omnichannel environments (desirable)
Experience with dbt or comparable data transformation and orchestration tooling (desirable)
Experience supporting analytics, machine learning or artificial intelligence use cases (desirable)
Experience working with ERP, point of sale, product, inventory, pricing, customer, ecommerce or marketing platforms (desirable)
Experience working with specialist consultancies, implementation partners or managed service providers (desirable)
Relevant Google Cloud or data engineering certification (desirable)

Benefits

Comp & perks

Permanent full-time employment
Hybrid working arrangement
Travel to other Mulberry offices and locations as business needs require
Opportunity to support sustainability initiatives through Mulberry’s Made to Last strategy
Inclusive and respectful workplace culture
Support for knowledge transfer and capability development