DE-RCE-Fraud Analytics-Senior-G (Delhi)

At EY, youll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Primary Technical Skills Critical Technical Skills Python (Required) - Strong experience building applications, automation, analytical tooling, and fraudrelated data processing workflows. AWS (Required) - Hands-on experience with core AWS services for data processing and orchestration (Lambda, S3, Glue, Step Functions, EventBridge). - Ability to design and scale fraudrelated data pipelines and event-driven architectures. Visualization (Required) - Advanced skills in Tableau and/or Python visualization libraries to support fraud insights, anomaly detection, and rule performance monitoring. SQL (Required) - Ability to write productive queries for large and complex fraud or transaction datasets, including advanced joins, window functions, and performance tuning. Primary Non-Technical Skills Data Analyst, Specialist Role Overview The Senior Data Analyst, Specialist leads complex analytical and data engineering initiatives in support of Fraud Analytics and Fraud Operations across ES&F.; This role is highly technical, combining advanced Python development, AWS data engineering, and fraudfocused analytical storytelling. The ideal candidate has significant fraud experience within financial services, banking, or fintech, and can build scalable analytical solutions that strengthen fraud prevention, detection, and operational efficiency. Key Responsibilities Advanced Data Engineering & Application Development - Design, build, and maintain Python-based applications, tools, and automated analytical workflows that support fraud detection, monitoring, and reporting. - Develop and manage AWS data pipelines (Lambda, S3, Glu .