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Our business frameworks team are an engaged and dynamic group of professionals who play a crucial role in creating the core elements of the Avaloq Banking Suite, which serve numerous Global banking clients. Our primary focus areas include: Business Process Management: Streamlining and improving the banks' internal processes to enhance efficiency; Object Framework: Maintain and improve the framework which stores banking data as objects in the underlying database; Rule Engines: Maintaining and improving systems that automate decision-making processes based on predefined rules.
Job Responsibility:
Closely collaborate with the Team Lead, Product Owner, Team Architect and other Software Engineers
Write solution designs for new developments and have them reviewed with our technical leads and architects
Participate in client workshops and support our business analysts in requirements analysis
Design, develop and maintain thought-out solutions within the team’s responsibility
Improve and optimize existing functionalities
Develop and maintain automated tests, quality insurance
Take ownership and responsibility for your area of expertise
Work with agile mindset, process and ticketing platforms (Jira)
Requirements:
Strong evidence-able continuous relevant software development experience
Experience of working with database technologies (SQL, Oracle PL/SQL)
Java programming language and frameworks
Eager to learn and understand the business needs aiming to provide clean designs and high-quality code
Strong conceptual and analytical mind with a structured and autonomous approach to work on complex technical and business problems
Nice to have:
University degree in Computer Science or related discipline
Interest in maintaining Rule Engines
Good understanding of Java, Spring framework and Spring Boot, Hibernate/JPA, SQL
Experience with developing Domain-specific languages (DSLs)
Knowledge / experience in Git, Gradle, Jenkins
What we offer:
Annual bonus
Flexible working
Instant recognition
Access to Udemy for professional and personal learning