Data Engineer (FMCG / Food / Retail industry exper

KEY RESPONSIBILITIES: Data Integration & Pipeline Development

• Design, develop and maintain reliable ETL/ELT data pipelines across multiple business systems.
• Integrate data from systems such as ERP, TMS, WMS, finance, CRM, supply chain, HR and other business applications.
• Reduce reliance on manual data extraction and manipulation through effective automation.
• Ensure data pipelines are scalable, efficient and appropriate for the organisation's future data requirements.
• Work closely with Data & Systems Architecture to ensure engineering solutions align with broader technology and architecture standards.

Data Quality, Integrity & Reliability

• Implement automated data-quality checks and validation controls.
• Assist with the implementation of MDM across the organisation.
• Identify and investigate inconsistencies, missing data, duplication and other data-quality issues.
• Work with system owners and business stakeholders to address root causes of data-quality problems.
• Monitor data pipelines and integration processes to identify failures or performance issues.
• Troubleshoot and resolve data-processing and integration errors.
• Ensure that data used for reporting and analysis is accurate, complete, consistent and available when required.
• Support the development of a trusted organisational data environment.

Analytics & Business Intelligence Enablement

• Develop and maintain analysis-ready datasets for Data Analysts, Analyst Developers and other authorised business users. • Support the development of reliable data models for dashboards, management reporting and business intelligence solutions. • Assist analysts with complex data extraction, transformation and integration requirements. • Ensure that commonly used business information is sourced from controlled and consistent datasets. • Enable greater self-service, democratized analytics through well-structured and governed data. The Data Engineer's primary responsibility is to build and maintain the data foundation rather than own business reporting or interpretation of business performance.

Automation & Continuous Improvement

• Review existing data flows and recommend improvements.
• Optimise database queries, pipelines and processing routines to improve performance.
• Proactively identify opportunities where improved data integration can simplify business processes.
• Contribute to continuous improvement initiatives within Business Transformation.
• Migrate data warehouse, data lake or similar data structures where applicable.

Business Transformation & Systems Projects

• Participate in bu

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