Data Engineer for Fraud Analytics

To support advanced fraud analytics and investigative solutions, the full-time remote Data Engineer for Fraud Analytics will design, build, and maintain scalable data pipelines while collaborating with cross-functional teams to ensure high-quality data integration and analytics. Key responsibilities Design, develop, maintain, and optimize scalable ETL pipelines for advanced analytics and investigative workloads Ingest and transform structured and unstructured data from diverse sources, including APIs and databases Implement data quality validation and monitoring processes to ensure data reliability throughout the analytics lifecycle Required qualifications Must have experience with Fraud Analysis Three or more years of professional experience in data engineering or a related technical field Demonstrated experience designing and optimizing scalable ETL pipelines across diverse data sources Strong SQL and Python programming skills for data ingestion and transformation Experience with cloud-based data platforms such as Databricks Unity Catalog or SQL Server managed instances