Data Engineer - Fraud Detection

To support advanced analytics and fraud detection initiatives, the fully remote Data Engineer - Fraud Detection will design, build, maintain, and optimize data pipelines to ensure reliable, high-quality data for fraud detection and investigative analysis across large-scale federal benefit programs. Key Responsibilities Design, build, and optimize scalable ETL and ELT pipelines from diverse data sources for advanced analytics Support data engineering activities within modern Lakehouse architectures and manage data within platforms like Databricks and SQL Server Implement data quality checks and lineage practices to ensure data reliability and transparency throughout the pipeline Required Qualifications Minimum three (3) years of professional experience in data engineering or a related field Strong SQL and Python skills or equivalent programming experience Experience with ETL pipeline development and data ingestion from various sources including APIs and graph databases Familiarity with modern Lakehouse architectures and data quality processes Experience collaborating with cross-functional technical teams and stakeholders