Data Specialist - Data Analytics Engineer

Overview

In this role, you will shape the data foundation that informs decision-making across Morrisons. You’ll design and manage data models and a central semantic layer on Google Cloud, bridging pipelines and business insight. You’ll collaborate with analysts and stakeholders to ensure reliable, well-documented data for reporting and analytics. Expect a hands-on role that blends data architecture, governance, and delivery in a fast-paced retail environment.

Pay / Benefits

• 15% discount in store
• Annual bonus scheme
• Career progression and development opportunities
• Generous holiday entitlement
• Market leading pension scheme and life assurance
• Private healthcare

Responsibilities

• Translate business needs into robust data architecture and optimised analytical datasets
• Own data model delivery for the domain, with accurate documentation and definitions
• Champion data literacy and standard transformation guidelines across the organisation
• Mentor trainees on SQL standards, data testing, version control, and domain context
• Facilitate communication between engineering teams and non-technical stakeholders
• Build reusable conformed data layers to reduce processing waste and cloud costs
• Design, test, and deploy secure data models and transformations in Google Cloud Platform
• Maintain the centralised semantic layer (e.g. LookML or similar) for consistent definitions across reporting
• Map enterprise ontologies to relational models reflecting retail and supply chain processes
• Implement metadata repositories, data dictionaries, and lineage tools
• Define test conditions and run automated data quality checks
• Refine models to adapt to changes in operations and priorities

Key requirements

• Data Modelling with recognised patterns (Kimball, Inmon, dimensional modelling)
• Semantic Layer Architecture and centralised metrics layers
• Domain mapping from ontologies to dimensional schemas
• Advanced SQL for profiling, transformation, and performance tuning
• Data Transformation & CI/CD with tools like Dataform and Git/Jenkins
• Data Quality & Testing with automated validation scripts
• Metadata & Documentation management (data dictionaries, cataloging)
• Stakeholder translation of complex data structures
• Experience with Agile/Waterfall delivery frameworks

• Stakeholder communication
• Mentoring and coaching
• Collaborative mindset
• Data Modelling
• Semantic Layer Architecture
• Domain Mapping