Key Responsibilities

• Data Engineering & Automation: Design, develop and optimise data pipelines, automating manual processes to improve efficiency, scalability and reliability.
• ETL Development: Deliver ETL technical design, data extraction, transformation and loading, ensuring accurate and efficient data integration.
• Data Quality & Governance: Perform data quality testing, cleansing, validation and monitoring to maintain data integrity and regulatory compliance.
• Data Warehousing & Modelling: Develop and maintain data models and warehousing solutions to support business reporting and analytics.
• Data Sourcing & Analysis: Identify, source and explore new datasets using appropriate tools and technologies.
• Streaming Data: Support the development of streaming data ingestion and transformation solutions, aligned with the organisation's data strategy.
• Continuous Improvement: Introduce modern data techniques, automation and development best practices through collaboration, training and experimentation.
• Stakeholder Engagement: Work closely with technical teams, business users and senior stakeholders to understand requirements and deliver effective data solutions.
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Key Responsibilities

• Data Engineering & Automation: Design, develop and optimise data pipelines, automating manual processes to improve efficiency, scalability and reliability.
• ETL Development: Deliver ETL technical design, data extraction, transformation and loading, ensuring accurate and efficient data integration.
• Data Quality & Governance: Perform data quality testing, cleansing, validation and monitoring to maintain data integrity and regulatory compliance.
• Data Warehousing & Modelling: Develop and maintain data models and warehousing solutions to support business reporting and analytics.
• Data Sourcing & Analysis: Identify, source and explore new datasets using appropriate tools and technologies.
• Streaming Data: Support the development of streaming data ingestion and transformation solutions, aligned with the organisation's data strategy.
• Continuous Improvement: Introduce modern data techniques, automation and development best practices through collaboration, training and experimentation.
• Stakeholder Engagement: Work closely with technical teams, business users and senior stakeholders to understand requirements and deliver effective data solutions.
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