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We’re looking for a skilled Data Engineer to build, optimise and maintain high-performing data pipelines across Microsoft Fabric and GCP. You’ll play a key role in ensuring reliable, production-ready data is delivered to support business-critical analytics. Working within a modern lakehouse environment, you’ll focus on automation, data quality, and performance, helping to drive efficient and scalable data operations.
Job Responsibility:
Develop and maintain ETL/ELT pipelines to ingest data from multiple sources into Fabric/GCP
Monitor pipeline performance, troubleshoot issues, and act as a key responder for incidents
Embed data quality checks to ensure accuracy and integrity of data outputs
Optimise SQL and Python code to improve performance and reduce cloud costs
Support data governance and documentation, ensuring pipelines are transparent and supportable
Enable Analytics and Data Science teams with trusted, accessible datasets
Contribute to the migration of legacy data processes into modern, scalable solutions
Requirements:
Strong experience with SQL (including optimisation) and Python for data engineering
Hands-on experience working with GCP (BigQuery) and/or Microsoft Fabric (Synapse/OneLake)
Experience building and managing data pipelines and workflow orchestration tools (e.g. Airflow, Data Factory)
A solid understanding of data modelling (e.g. star schemas, SCD) and governance principles
Experience implementing data quality testing and validation
Familiarity with CI/CD and version control (e.g. Git, GitHub Actions, Azure DevOps)
Knowledge of cloud security principles and working within governed environments
A proactive approach to monitoring, alerting, and resolving data issues
Comfortable working in an Agile environment, collaborating with stakeholders, and clearly communicating technical challenges to non-technical audiences
What we offer:
20% staff discount, which increases with length of service
Thrive Recognition Scheme
Wellbeing support provided by the Retail Trust
Life Assurance
Retail Rewards platform offering discounts for other retailers