Expert Data Engineer

Quick Facts

• Role: Expert Data Engineer

Description

Design and optimize data pipelines supporting end-to-end Capital Markets AML detection scenarios. Implement detection logic, rule frameworks, and scoring components for financial-crime use cases, while ensuring high-quality engineering across code, pipelines, and operational solutions. Work in Agile teams in a fast-paced environment.

Responsibilities

• Design, implement, and optimize data pipelines for Capital Markets AML detection scenarios

• Implement detection logic, rule frameworks, and scoring components for financial-crime use cases

• Ensure high-quality engineering across code, data pipelines, and operational solutions

Requirements

• Strong programming skills in Python and Java

• Advanced experience with Apache Spark, PySpark, Spark SQL, and SQL for large-scale distributed data processing

• Proven experience with distributed compute platforms and on-premise cluster environments

• Proficiency with CI/CD tools such as Bamboo/Jenkins and Bitbucket

• Experience working in Agile teams and independently in fast-paced, evolving environments

• Strong analytical and problem-solving skills and ability to adapt quickly

• Very good command of English (spoken and written)

Nice to have

• Understanding of Capital Markets products (FX, Equities, Derivatives, Bonds)

• Experience in Financial Crime, AML, or surveillance use cases

• Experience implementing rule-based detection systems, scorecards, or alerting frameworks

• Experience delivering NFRs covering performance, scalability, observability, data quality, resiliency, and security

• Experience with automation (automated pipeline deployment, data validation, testing frameworks, workflow orchestration)

• Experience integrating with third-party systems, including case management systems

• Ability to collaborate effectively across cross-functional teams