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.
- Solid 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.

Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading staffing and recruiting powerhouse. Proudly recognized as a nationally and locally certified diversity firm, Cynet delivers agile, scalable talent solutions across industries. With an active footprint in all 50 U.S. states and Canada, we support thousands of consultants through our expansive, high-performing recruitment engine operating across North America and Asia ensuring speed, quality, and consistency in every hire.

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