We are looking for a seasoned Data Architect / Data Management Lead with extensive experience in designing data solutions for fraud analytics, investigative platforms, or intelligence and case management systems. The successful candidate will oversee the architecture, development, and implementation of integrated data pipelines and analytics frameworks within SAS-based environments, particularly SAS Viya. This is a hands-on leadership role requiring both technical depth and strong stakeholder coordination across business and technology teams.

Responsibilities:

• Partner with business analysts to understand and shape data requirements for fraud or investigative systems.
• Architect end-to-end data strategies, from source acquisition and cleansing to storage, preparation, and analytics delivery.
• Convert functional needs into technical deliverables across ETL, engineering, and reporting layers.
• Design and manage real-time and batch ingestion workflows into SAS platforms or large-scale data lakes.
• Build and maintain robust data pipelines, orchestration layers, and visualization components using SAS Viya, DS2, Python, and other tools.
• Coordinate testing, integration, and support activities, including UAT and post-deployment maintenance.
• Lead documentation efforts and contribute to overall data governance, metadata, and quality frameworks.
• Troubleshoot complex data issues and track project progress against delivery milestones.

Required Experience & Skills:

• Minimum 10 years of experience in data architecture, analytics platforms, or BI/data warehouse implementations.
• Delivered at least 5 full-scale projects involving fraud detection, surveillance systems, or case/investigation platforms.
• Strong hands-on capabilities in:
  SAS Viya, SAS DS2, and SQL
  Python, Spark, JSON, XML
  Linux, job orchestration tools, and real-time technologies like Kafka or SAS ESP
  Postman, SOAPUI, REST APIs, and CI/CD frameworks (DevOps / DataOps)
• Familiar with:
  Data modeling, source-to-target mapping, real-time processing design
  Metadata and data lineage tools, orchestration frameworks
• Experience with SAS Intelligent Decisioning, RTDM, PEGA, or similar decision management tools is advantageous.
• Prior involvement in public sector, government, or regulatory environments is preferred.
• Strong communication and stakeholder alignment skills; capable of leading technical teams.
• Bachelor's degree in a relevant discipline such as Computer Science, Information Technology, or Statistics