Description

Job Description:
We are seeking a Big Data Developer to build and enhance realtime and batch fraud analytics AML platforms that process high volume financial transactions The role focuses on developing scalable data pipelines that support transaction monitoring alert generation investigations and regulatory compliance

Key Responsibilities
Design and build realtime 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
Ensure data quality traceability and audit readiness to meet regulatory requirements
Optimize performance for lowlatency high through put fraud use cases
Support alert data generation and downstream analytics investigation platforms
Monitor and troubleshoot production data pipelines in secure environments
Collaborate with fraud risk compliance and downstream application teams

Required Skills
Strong experience with Apache Spark Core SQL Streaming
Hands on expertise in Kafka or realtime event streaming frameworks
Hadoop ecosystem HDFS Hive
Programming in Python, Scala, Java
Strong SQL and data processing skills
Experience working in Linux/Unix environments

Preferred Skills
Experience in fraud detection AML transaction monitoring or CAMPS systems
Exposure to banking regulatory environments
Cloud platforms Azure AWS
NoSQL databases HBase Cassandra MongoDB
Workflow orchestration tools Airflow Oozie

Key Skills

Education

Any Graduate