Br /br /Data Engineerbr /br /br /Location: brussels - montagne du parc / warandebergbr /br /br /Work model: Hybrid (50% onsite / 50% remote)br /br /br /Must reside in belgium and hold the right to work in belgiumbr /br /br / br /br /br / br /br /br /We are looking for an Expert Data Engineer to join the banking/insurance domain. You will play a key role in designing, developing, and optimizing large-scale data solutions, working on complex, high-volume environments (20tb+ databases).br /br /br / br /br /br /This role combines deep technical expertise, hands-on problem solving, and close collaboration with business and IT stakeholders.br /br /br / br /br /br /Key responsibilitiesbr /br /br /br /Design, develop, and optimize ETL pipelines using Informatica PowerCenter for large-scale data processingbr /br /Work with very large databases (20tb+) on Oracle and Sybase IQ, ensuring performance and reliabilitybr /br /Develop and maintain Java-based applications (Java, Spring Boot, Maven)br /br /Collaborate closely with Business Analysts to translate business requirements into robust technical solutionsbr /br /Take ownership of release management, securing complex changes while enforcing coding standards and best practicesbr /br /Perform performance tuning of batch processing, scheduling, and monitoring systemsbr /br /Actively troubleshoot issues with a pragmatic, hands-on mindset and continuously improve processesbr /br /Contribute effectively in a cross-cultural, English-speaking team environmentbr /br /br /br / br /br /br /Required skills experiencebr /br /br /br /Minimum 6 years of experience in data analytics / data engineering rolesbr /br /Strong expertise in ETL development, specifically Informatica PowerCenterbr /br /Advanced SQL skills, including complex query design and performance optimizationbr /br /Solid knowledge of Java (Java, Spring Boot, Maven) with the motivation to further develop this skillsetbr /br /Experience with batch processing, scheduling, dependency management, and monitoringbr /br /Proven ability to work with large-scale, high-performance data environmentsbr /br /Bachelor#39;s degree in a quantitative discipline (Computer Science, Engineering, Mathematics, Statistics, etc.)br /br /br /br / br /br /br /Nice-to-have:br /br /br /br /Experience with automationbr /br /Exposure to CI/CD pipelines or DevOps practicesbr /br /Knowledge of data governance or regulatory compliance (e.g., GDPR)br /