Job Summary:

We are seeking a highly experienced Data Architect / Data Management Lead with strong domain knowledge in fraud analytics, case management, and investigation/intelligence systems. The ideal candidate will lead the design, development, and deployment of data integration and analytics components within SAS environments, with hands-on exposure to SAS Viya, data pipelines, and real-time streaming tools. This role is ideal for someone who thrives at the intersection of data strategy, architecture, and stakeholder collaboration.

Key Responsibilities:

• Collaborate with business analysts to gather and interpret data-related requirements for fraud/case management/investigation solutions.
• Define and implement a comprehensive data architecture, including data sourcing, integration, cleansing, storage, and provisioning strategies.
• Translate business requirements into technical work products across the ETL, data engineering, and reporting layers.
• Design and lead batch and real-time data ingestion processes from various sources into SAS or big data platforms.
• Develop data pipelines, orchestration frameworks, and visualization/reporting structures using tools such as SAS Viya, DS2, and Python.
• Lead integration and testing of developed components, and support UAT activities.
• Oversee documentation, project tracking, and technical troubleshooting.
• Ensure compliance with data governance, metadata, and quality management standards.

Experience & Skills Requirements:

• 10+ years of relevant experience in Business Analytics, Data Architecture, or Data Warehousing.
• Proven end-to-end delivery of at least 5 enterprise projects, preferably involving SAS solutions in fraud, surveillance, or case management domains.
• Strong hands-on experience in:

1. SAS Viya, SAS DS2, SQL Programming
2. Python, Spark, JSON, XML
3. Job scheduling, Linux commands, data streaming tools (Kafka/SAS ESP)
4. Postman/SOAPUI, REST APIs, DevOps/DataOps

• Working knowledge of:

1. Data model design, source-to-target mapping
2. Real-time event processing, metadata management, and orchestration

• Background in fraud analytics, investigative systems, or intelligence/case management frameworks is essential.
• Familiarity with tools such as SAS Intelligent Decisioning, RTDM, PEGA, or similar is a strong plus.
• Experience working in government, public sector, or regulated environments is highly preferred.
• Strong communication, stakeholder management, and leadership skills.
• Degree in Computer Science, IT, Statistics, or related field.