Data Engineer - Fraud Detection

Job Summary

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