We are seeking a hands-on Data & Information Architect to lead the data architecture strategy for an enterprise Testing & Monitoring (TANDMS) platform supporting Corporate Risk and Governance, Risk & Compliance (GRC). This role is ideal for an experienced architect who can drive initiatives from concept through architecture, design, and working prototypes while ensuring scalable, governed, and AI-enabled solutions.
The ideal candidate will bring deep expertise in enterprise data architecture, financial services, modern integration technologies, and AI-enabled information management.
Define and own the enterprise data and information architecture strategy for the Testing & Monitoring platform.
Design conceptual, logical, canonical, semantic, and business data models across GRC domains including Risk, Control, Obligation, Issue, Test, Process, and Evidence.
Establish authoritative systems of record and define source-to-target mappings, data lineage, metadata, governance, reconciliation, and auditability.
Design scalable data ingestion and integration using APIs, ETL/ELT, Kafka/event streaming, data virtualization, and cloud data platforms.
Develop reusable data products and metadata-driven integration patterns.
Enable configurable testing, automated evidence collection, control effectiveness measurement, and regulatory traceability.
Design and implement knowledge graph and ontology-based solutions using Neo4j or similar technologies for impact analysis and cross-domain intelligence.
Embed AI capabilities including GenAI, LLMs, RAG, agentic AI, and intelligent automation for anomaly detection, evidence summarization, predictive issue identification, and obligation-to-control mapping.
Collaborate with business, risk, compliance, engineering, and enterprise architecture teams.
Present architectural solutions to executive leadership and Architecture Review Boards.
Drive proof-of-concepts and working prototypes while ensuring governance, security, privacy, and Responsible AI compliance.
7+ years of experience in solution, enterprise, or data architecture.
5+ years of experience within Financial Services, Banking, Capital Markets, Insurance, or Risk & Compliance.
Strong expertise in enterprise data architecture, information architecture, and data governance.
Experience with conceptual, logical, canonical, semantic, and business data modeling.
Strong knowledge of APIs, Kafka/event streaming, ETL/ELT, data virtualization, Lakehouse architecture, and cloud/object storage.
Experience with data lineage, metadata management, reconciliation, auditability, and authoritative data sources.
Hands-on experience implementing AI solutions including GenAI, LLMs, RAG, or agentic AI.
Experience with enterprise integration patterns and scalable distributed architectures.
Strong executive communication and stakeholder management skills.
Experience working independently in complex enterprise environments.