Description

What's the Job?

• Design and develop scalable data pipelines using Python and PySpark to support financial crimes initiatives.
• Support modernization efforts by transitioning legacy data workflows to modern distributed data processing frameworks.
• Build and optimize large-scale data processing solutions for AML, investigations, sanctions, fraud, and KYC use cases.
• Collaborate with engineering and business teams to support AML, compliance, and risk platforms.
• Ensure data quality, performance, and scalability across extensive datasets, maintaining high standards of data governance.

What's Needed?

•  Experience in software or data engineering roles.
• Hands-on expertise with Python, PySpark, SparkSQL, and relational databases such as Oracle, DB2, SQL Server, or Teradata.
• Experience building enterprise-grade data pipelines and working within regulated financial environments.
• Strong understanding of distributed data processing, performance tuning, and data governance concepts.
• Excellent communication skills to effectively collaborate across technical and business teams

Key Skills

Education

Any Graduate