Job Overview:

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 ETLELT workflows supporting customer transaction and risk datasets.

- Ensure data quality traceability and audit readiness to meet regulatory requirements.

- Optimize performance for lowlatency highthroughput fraud use cases.

- Support alert data generation and downstream analyticsinvestigation 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.

- Handson expertise in Kafka or realtime event streaming frameworks.

- Hadoop ecosystem HDFS Hive.

- Programming in Python Scala Java.

- Robust SQL and dataprocessing skills.

- Experience working in LinuxUnix 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.

📌 Big Data Developer (Ontario)
🏢 Cynet Systems
📍 Ontario