Data Engineer

Key Responsibilities • Design, develop, and maintain scalable data pipelines to support business intelligence, analytics, and operational reporting. • Build and optimise ETL/ELT processes to integrate structured and unstructured data from multiple internal and external data sources. • Develop and maintain data models, data warehouses, and data lakes to support enterprise data management. • Ensure data quality, integrity, security, and governance across the organisation's data platforms. • Collaborate with software engineering, product, analytics, and business stakeholders to understand data requirements and deliver reliable data solutions. • Monitor, troubleshoot, and optimise data pipeline performance to ensure high availability and scalability. • Implement data validation, monitoring, and automation processes to improve operational efficiency. • Support cloud-based data platform initiatives and contribute to data architecture improvements and technology enhancements. • Prepare technical documentation, data dictionaries, and operational procedures for data engineering solutions. • Stay current with emerging technologies and recommend improvements to enhance the organisation's data capabilities. Required Skills & Experience • Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related discipline. • At least 10 years of experience in data engineering, data integration, or related technical roles. • Strong experience designing and maintaining ETL/ELT pipelines and enterprise data solutions. • Proficiency in SQL and programming languages such as Python, Java, or Scala. • Experience with relational and NoSQL databases, data warehousing concepts, and cloud-based data platforms. • Familiarity with big data technologies and modern data engineering frameworks. • Strong analytical and problem-solving skills with the ability to troubleshoot complex data issues. • Good understanding of data governance, security, and data quality best practices. • Strong communication and stakeholder management skills with the ability to work effectively in cross-functional teams. Nice to Have • Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform. • Experience with Apache Spark, Kafka, Airflow, or similar data engineering technologies. • Knowledge of DevOps, CI/CD, and infrastructure automation practices. • Experience supporting AI, machine learning, or advanced analytics initiatives. • Experience working in financial services, fintech, insurance, or technology organisations.