Design and implement scalable data models supporting operational and analytical reporting, including Bronze, Silver, and Gold data layers in line with Medallion architecture
Apply dimensional modelling techniques (Star/Snowflake schemas) to support business intelligence requirements and own semantic models for end-user reporting tools
Build, optimise, and maintain ETL/ELT pipelines ingesting data from multiple source systems (ERP, CRM, supply chain systems)
Engineer robust processes for transforming complex and semi-structured data (including JSON) into structured datasets
Develop logic to parse, cleanse, and standardise raw data into reliable, analytics-ready formats; monitor and validate data quality across all pipeline stages
Implement data validation, reconciliation, and error-handling mechanisms
Support migration from legacy systems to modern cloud-based platforms (e.g. Microsoft Fabric or similar) and optimise SQL queries and data refresh processes
Work closely with BI developers, analysts, and business stakeholders to understand reporting and data needs, translating requirements into technical data solutions
Contribute to data governance practices including documentation, standards, and lineage tracking

Minimum 5+ years' experience in data engineering or a similar role
Proven experience building and maintaining ETL/ELT pipelines in a commercial environment
Experience working with large-scale datasets, ideally in retail, wholesale, distribution, or supply chain environments
Demonstrated experience working with cloud-based data platforms
Advanced proficiency in SQL for data transformation and performance tuning
Strong experience with data transformation tools (e.g. Power Query, dbt, or similar)
Proficiency in Python for data processing and automation
Experience with Microsoft Fabric or similar platforms (Azure Synapse, Databricks, Snowflake)
Strong understanding of Medallion architecture and data lakehouse concepts
Experience working with semi-structured data formats (e.g. JSON, XML)
Knowledge of data modelling techniques (Star/Snowflake schemas)
Experience with Power BI or similar BI tools
Strong problem-solving, analytical, and communication skills with the ability to translate technical concepts to non-technical stakeholders
Bachelor's degree in Computer Science, Information Technology, Data Engineering, or related field preferred; relevant cloud certifications highly regarded
Coachable mindset—eager to validate AI-generated code and understand when to seek human guidance on technical decisions

Data Engineer

Key skills