The project focuses on building a Transaction Monitoring solution designed to support the detection of money laundering activities (AML) within the Capital Markets domain. It is a greenfield initiative, providing the opportunity to design and develop the system architecture from the ground up, with a strong emphasis on innovation, product ownership, and delivery excellence.

Hybrid working model with 3 days per week on-site

Java Python IT Developer Expert

Your responsibilities

• Designing, implementing, and optimizing data pipelines supporting end-to-end AML detection scenarios in the Capital Markets domain, leveraging Apache Spark (PySpark) and SQL for large-scale data processing in distributed environments
• Developing and maintaining applications in Python and Java for transactional data processing and implementation of complex business logic
• Building and maintaining CI/CD pipelines using Bamboo/Jenkins and Bitbucket to automate deployment, testing, and delivery processes
• Working with distributed computing platforms and on-premise clusters, focusing on performance optimization and scalability in big data environments
• Actively contributing to the design and development of a greenfield architecture, with a strong sense of product ownership, innovation, and delivery quality

Our requirements

• Strong programming skills in Python and Java.
• Advanced experience with Apache Spark (PySpark), SQL for large-scale distributed data processing.
• Hands-on experience in distributed compute platforms and on-premise cluster environments.
• Proficiency with CI/CD tools such as Bamboo/Jenkins, and Bitbucket.
• Experience working in Agile teams, with the ability to work independently in fast-paced, evolving environments.
• Strong analytical and problem-solving skills with the ability to adapt quickly.
• Understanding of Capital Markets products including FX, Equities, Derivatives, and Bonds etc.
• Previous experience in Financial Crime, AML, or surveillance use cases.
• Experience implementing rule-based detection systems, scorecards, or alerting frameworks.
• Experience delivering against NFRs such as performance, scalability, observability, data quality, resiliency, and security.
• Experience with automation, including automated pipeline deployment, data validation, testing frameworks, and workflow orchestration.
• Experience in integrating the solutions with the third party systems (like case management systems).
• A strong “can-do” attitude and the ability to collaborate effectively in a cross-functional team.