• Define, implement, and maintain enterprise data architecture principles, standards, policies, and target-state architectures aligned with business and technology strategies. • Design and govern current-state, transition-state, and target-state data architectures and data flows across multiple business domains. • Develop and maintain enterprise data models, ensuring alignment with industry standards and organizational data architecture principles. • Review and approve data architecture artefacts, ensuring compliance with enterprise governance, policies, standards, and best practices. • Establish and support enterprise data governance functions, architecture review boards, and governance forums, including developing Terms of Reference (ToRs). • Provide architectural leadership and guidance for strategic data initiatives, enterprise data platforms, and data product development. • Collaborate with business stakeholders, enterprise architects, solution architects, and engineering teams to define scalable and future-ready data solutions. • Evaluate and recommend enterprise data architecture methodologies, technologies, and tools to support business transformation. • Promote adoption of modern data architecture approaches, including Data Lake, Data Mesh, Data Fabric, Hybrid Architectures, and AI-enabled data ecosystems. • Drive continuous improvement by identifying opportunities to enhance enterprise data architecture capabilities, governance, and operating models. • Stay informed of emerging technologies, industry trends, and regulatory developments to ensure the organization's data architecture remains current and effective.

• Build and manage data pipelines: ingestion from APIs/files, transformations across layers, schema evolution, and collectors from 10+ external sources • Design semantic models and hybrid search for AI; own star schema with bridge tables and performance optimization • Enforce governance: access controls, licensing registry, quality monitoring, and retention for GDPR/CCPA • Manage cloud infrastructure, monitoring, SLAs, cost optimization, and CI/CD • Deliver client views, multi-cloud exports, and partner with delivery teams for dashboards and AI tools

• Define, implement, and govern enterprise data architecture standards, policies, and frameworks across the assigned business domain • Ensure data architecture artefacts, data products, and data deliveries comply with enterprise governance, quality, and regulatory requirements • Lead domain data modelling activities and ensure alignment with enterprise and global data models • Develop and maintain current, transition, and target-state data architectures and data flows across business domains • Drive architecture decisions for enterprise data platforms, analytical solutions, and strategic data initiatives • Establish and facilitate data governance forums, architecture review boards, and decision-making processes • Collaborate with business stakeholders, data owners, technology teams, and enterprise architects to align on data standards and architecture roadmaps • Provide architectural leadership for regulatory reporting and business transformation initiatives across Risk, Finance, Treasury, Compliance, or Transaction Banking domains • Review and approve solution and data architecture artefacts to ensure adherence to enterprise standards and best practices • Monitor emerging technologies and modern data architecture trends, recommending innovative solutions that support the organization's strategic objectives • Contribute to the development of enterprise data strategy, governance capability, and future-state architecture roadmaps • Promote the adoption of enterprise data governance, metadata management, and data quality practices across the organization

• Own and self-heal our fleet of web scrapers • Keep daily scraping runs stable—monitoring, alerting, retries, and graceful handling of upstream failures • Use LLMs for resilient parsing and entity extraction from messy or changing HTML • Own and optimize the serving layer and the ETL/ELT pipelines feeding our BigQuery warehouse • Build our reporting infrastructure—data models, transformations, and dashboards • Drive data quality through rule-based checks and ML/LLM-based anomaly detection • Build and maintain production-grade MCP servers and agentic workflows