Data Architect

Design and implement enterprise-scale data architectures supporting Fraud, Risk, and Compliance reporting platforms. Define logical and physical data models for fraud analytics, transaction monitoring, alert management, and case management systems. Architect and optimize data lakes, data warehouses, and reporting solutions to enable near real-time fraud insights. Collaborate with business stakeholders, fraud operations teams, data scientists, and technology teams to translate business requirements into scalable data solutions. Drive data governance, lineage, metadata management, and data quality initiatives across fraud data domains. Design integration frameworks between source systems, fraud platforms (e.g., Actimize, SAS, FICO), reporting tools, and downstream analytics applications. Support regulatory and management reporting requirements related to fraud, AML, financial crime, and operational risk. Ensure architecture compliance with enterprise security, privacy, and data governance standards. Provide architectural guidance for cloud migration and modernization initiatives.

Technical Strong expertise in Enterprise Data Architecture and Data Modeling. Extensive experience in Data Warehousing, ETL/ELT, Data Lakes, and Analytics Platforms. Hands-on knowledge of SQL, PL/SQL, and performance optimization of large datasets. Experience with reporting and visualization platforms such as: Power BI Tableau Cognos QlikView/Qlik Sense Experience with cloud data platforms: Azure Data Platform AWS GCP (preferred) Knowledge of Hadoop, Spark, Databricks, and modern data engineering frameworks. Understanding of data governance, lineage, metadata management, and data quality frameworks. Domain Strong experience in Banking and Financial Services. Proven background in: Fraud Detection & Prevention Transaction Monitoring Fraud Operations Analytics Risk & Control Reporting Financial Crime / AML Reporting Understanding of regulatory and compliance reporting requirements in financial institutions. Preferred Skills Experience with fraud platforms such as NICE Actimize, SAS Fraud Management, FICO Falcon, or equivalent. Exposure to AI/ML-driven fraud analytics and anomaly detection frameworks. Experience architecting real-time streaming and event-based analytics solutions., Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or related field. TOGAF, Azure Data Architect, AWS Data Analytics, or equivalent certifications preferred. Key Success Factors Strong stakeholder management and communication skills. Ability to influence senior business and technology leaders. Experience leading large-scale banking data transformation programs. Ability to balance architecture governance with delivery agility.