Data Engineer

• Design, build, and maintain ETL/ELT pipelines
• Ingest data from internal systems and external APIs
• Develop scalable data processing workflows (batch and/or real-time)
• Ensure pipelines are reusable, efficient, and maintainable
• Integrate data from various sources, including transactional flows
• Handle complex data scenarios such as: Event sequencing (e.g. bet → resolve), Idempotency and duplicate handling, Partial or delayed data
• Ensure consistency between source systems and analytical datasets
• Implement transformation logic aligned with architectural data models
• Build and maintain structured data layers for analytics consumption
• Collaborate closely with the Data Architect on model implementation
• Implement data validation, monitoring, and alerting mechanisms
• Identify and resolve data inconsistencies or failures
• Ensure high levels of data accuracy and availability
• Optimise pipelines for performance and cost-efficiency
• Support scaling of data infrastructure as volumes grow
• Ensure low-latency data availability where required
• Work closely with Data Architect, Analysts, and Manager
• Support Analysts by ensuring availability of curated datasets
• Contribute to continuous improvement of data platform capabilities