Description

Build and enhance real-time and batch fraud analytics and AML platforms that process high-volume financial transactions.

This role is hybrid.

Responsibilities

• Design and build real-time and batch data pipelines for fraud detection and AML monitoring.
• Process streaming transaction data using Apache Spark and Kafka.
• Develop ETL/ELT workflows supporting customer transaction and risk datasets.
• Optimize performance for low-latency, high-throughput fraud use cases.
• Ensure data quality, traceability, and audit readiness for regulatory compliance.

Required Skills

• 10+ years of experience in big data development.
• Strong expertise with Apache Spark (Core, SQL, Streaming).
• Hands-on experience with Kafka or real-time event streaming frameworks.
• Proficiency in Python, Scala, or Java.
• Strong SQL and data processing skills.
• Experience with Hadoop ecosystem (HDFS, Hive).
• Experience working in Linux/Unix environments.

Preferred Skills

• Experience in fraud detection, AML, or transaction monitoring systems.
• Exposure to banking regulatory environments.
• Cloud platform experience (Azure, AWS) and workflow orchestration (Airflow, Oozie).

Key Skills

Education

Any Graduate