Description

Design and develop scalable data pipelines using Python and PySpark to support financial crimes initiatives.

This role is on-site.

Responsibilities

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

Required Skills

• 5+ years of experience in software or data engineering roles.
• Hands-on expertise with Python and PySpark.
• Proficiency with SparkSQL.
• Experience with relational databases such as Oracle, DB2, SQL Server, or Teradata.
• Strong understanding of distributed data processing and performance tuning.
• Knowledge of data governance concepts within regulated financial environments.
• Ability to build enterprise-grade data pipelines.

Preferred Skills

• Excellent communication skills to effectively collaborate across technical and business teams.

Key Skills

Education

Any Graduate