Data Engineer (Financial Crimes, Disputes, and Risk (Fraud Focus))

Job Description: Data Engineer – Financial Crimes, Disputes, and Risk (Fraud Focus) Location: Cincinnati, OH (Onsite) Overview: We are seeking an experienced Data Engineer to join our Financial Crimes, Disputes, and Risk Information Technology team, with a strong focus on Fraud. This role will involve developing new data features, building and maintaining data integrations, and supporting data products in collaboration with senior engineers across disciplines. The position will be hands-on with ETL (DataStage) and Snowflake, playing a critical role in enabling fraud detection and risk management capabilities. Key Responsibilities: Design, build, and maintain scalable data integrations and pipelines using ETL tools (DataStage). Develop and optimize data products and solutions leveraging Snowflake. Partner with cross-functional teams to translate business and fraud detection requirements into technical solutions. Support ongoing data operations, troubleshooting, and system monitoring to ensure reliable performance. Contribute to the migration of data from legacy systems to modern platforms. Ensure compliance with internal security, governance, and regulatory requirements. Document technical designs, workflows, and architecture for knowledge sharing and operational efficiency. Provide support to team members and collaborate on continuous improvements to data architecture and engineering practices. Qualifications: Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent experience. Proven experience in data engineering with strong knowledge of ETL development (DataStage preferred). Hands-on expertise with Snowflake or other cloud-based data warehousing solutions. Proficiency in SQL and familiarity with additional programming languages (Python, Java, etc.). Experience with data modeling, integration, and migration. Knowledge of data governance, security, and compliance standards in financial services or highly regulated industries. Strong problem-solving skills with the ability to troubleshoot complex data issues. Excellent communication and collaboration skills. Preferred Skills: Experience working in Fraud, Financial Crimes, or Risk Technology domains. Exposure to big data platforms (e.g., Spark, Hadoop) or streaming frameworks (Kafka). Familiarity with machine learning workflows for fraud detection use cases.