<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <strong><strong>The Opportunity<br/><br/></strong></strong>We are supporting a major data platform transformation within a banking environment, moving from a legacy SQL Server and SSIS-based landscape to a modern data platform based on <strong>dbt, Dagster, and OpenShift</strong>.<br/><br/>This is an excellent opportunity for a motivated <strong>Junior Data Engineer</strong> who wants to grow into modern data engineering while working alongside experienced engineers on business-critical financial data platforms.<br/><br/>You will gain hands-on experience with modern data technologies, cloud-native platforms, and enterprise data engineering best practices in a highly regulated environment.<br/><br/><strong>What You Will Do<br/><br/></strong>You will support the implementation and operation of modern data pipelines while continuously expanding your technical skills.<br/><br/><strong><strong>Data Engineering<br/><br/></strong></strong><ul><li>Assist in translating legacy ETL processes into modern ELT pipelines using dbt</li><li>Support the development of Data Vault 2.0 models</li><li>Build and maintain data transformations and curated datasets</li><li>Contribute to data integration and migration activities<br/><br/></li></ul><strong><strong>Workflow &amp; Platform Operations<br/><br/></strong></strong><ul><li>Support workflow development using Dagster</li><li>Assist in deploying and monitoring workloads on OpenShift / Kubernetes</li><li>Participate in pipeline monitoring and operational support<br/><br/></li></ul><strong><strong>Data Quality<br/><br/></strong></strong><ul><li>Help implement automated data validation and testing</li><li>Support reconciliation between legacy and modern platforms</li><li>Investigate and resolve data quality issues together with senior team members<br/><br/></li></ul><strong><strong>Continuous Improvement<br/><br/></strong></strong><ul><li>Document technical solutions and operational procedures</li><li>Learn and apply software engineering best practices</li><li>Contribute ideas for improving performance and maintainability</li><li>Participate in code reviews and team knowledge sharing<br/><br/></li></ul><strong>Requirements<br/><br/></strong><strong><strong>Education &amp; Experience<br/><br/></strong></strong><ul><li>Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field (or equivalent practical experience)</li><li>Up to 3 years of experience in Data Engineering, Business Intelligence, Database Development, or Software Engineering</li><li>Internship or university project experience is also considered<br/><br/></li></ul><strong>Technical Skills<br/><br/></strong>Experience with some of the following technologies is desirable:<br/><br/><ul><li>SQL and relational databases (SQL Server is a plus)</li><li>Basic understanding of Python</li><li>Familiarity with dbt is an advantage</li><li>Understanding of data modelling concepts</li><li>Basic knowledge of Git version control</li><li>Interest in cloud platforms, Kubernetes or OpenShift</li><li>Exposure to ETL / ELT concepts<br/><br/></li></ul><strong><strong>Working Style<br/><br/></strong></strong><ul><li>Strong willingness to learn new technologies</li><li>Analytical thinking and problem-solving mindset</li><li>Structured and detail-oriented</li><li>Team player with good communication skills</li><li>Motivated to develop within a modern Data Engineering environment<br/><br/></li></ul><strong><strong>Nice to Have<br/><br/></strong></strong><ul><li>Basic knowledge of Data Vault concepts</li><li>Familiarity with Kafka or event-driven architectures</li><li>Exposure to Docker or Kubernetes</li><li>Experience with CI/CD concepts</li><li>Interest in financial services or banking environments</li></ul> </div>