Data Engineer

Role & responsibilities

• Design, develop and maintain scalable data pipelines and data processing systems.
• Build and optimise ETL/ELT workflows for extracting, transforming and loading data from multiple sources.
• Develop and maintain data warehouses, data lakes and modern data platforms.
• Integrate structured and unstructured data from internal and external systems.
• Design, implement and optimise database schemas, data models and data storage solutions.
• Work with large datasets to ensure data accuracy, consistency, availability and reliability.
• Develop and maintain batch processing and real-time data streaming solutions.
• Implement data quality checks, validation processes and monitoring mechanisms.
• Collaborate with data scientists, business analysts, software engineers and BI teams to support reporting and analytics requirements.
• Optimise SQL queries, database performance and data processing workloads.
• Implement data security, access controls, governance and compliance measures.
• Deploy and maintain cloud-based data solutions using AWS, Microsoft Azure or Google Cloud Platform.
• Work with distributed processing technologies and big data frameworks where required.
• Identify and resolve data pipeline failures, performance bottlenecks and integration issues.
• Automate data workflows, testing, deployment and operational monitoring.
• Maintain technical documentation, data dictionaries, pipeline specifications and architecture diagrams.
• Participate in technical design reviews and recommend improvements to data architecture.
• Support business intelligence, reporting, machine learning and advanced analytics initiatives.
• Coordinate with cross-functional teams to understand business requirements and translate them into technical data solutions.
• Mentor junior engineers and contribute to technical standards and best practices where required.

Preferred candidate profile

• Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, Software Engineering or a related technical discipline.
• 10-20 years of relevant professional experience in data engineering, data platform development, database engineering or related technical fields.
• Strong hands-on experience designing and implementing production-grade data pipelines and enterprise data solutions.
• Experience working with cloud platforms, data warehouses, ETL/ELT frameworks and large-scale data processing systems.
• Demonstrated ability to troubleshoot complex technical challenges and optimise data infrastructure.
• Experience in enterprise environments, large-scale projects or cross-functional technical teams will be an advantage.