VP System Analyst

The role spans requirements analysis, solution design,testing, implementation, and production support ensuring high-quality,scalable, and compliant data platforms that support advanced analytics and AIinitiatives. You will be responsible for end-to-end delivery of enterprise data andanalytics solutions leveraging traditional and modern Data architecture. Key Responsibilities • Lead end-to-end solution delivery for data and analytics across the full SDLC. • Analyze business and regulatory requirements, translate them into scalable solution designs & provide estimations. • Communicate complex technical and architectural concepts to business and senior stakeholders in a clear, simplified manner • Review and approve test strategies, functional test cases, and data validation approaches. • Manage risks and issues related to scope, data quality, regulatory commitments, and delivery timelines. • Participate in product and platform evaluations (RFPs, PoCs) for data, analytics, and AI tooling. • Partner with production support team to conduct root cause analysis, resolution, and preventive controls. • Drive productivity, efficiency & quality improvements across delivery and operational processes. • Lead innovation and modernization initiatives, including data discovery, cataloguing, governance, and AI enablement. • Ability to design data architectures supporting NLP and AI-driven analytics, including ingestion, curation, and governance of unstructured data within Data Lake, Data warehouse platforms. • Strong understanding of AI design governance, including explainability, lineage, confidence thresholds, and regulatory acceptability of AI-assisted insights. • Proven experience delivering large-scale analytics platforms within financial services spanning structured, semi-structured, and unstructured data • Ability to define data architectures and data flows that ingest, curate, and govern unstructured and semi-structured data within enterprise data platforms. • Strong experience defining and governing enterprise Data architectures to support batch, micro-batch, and near real-time analytics. • Ability to translate business, regulatory, and analytics requirements into logical data layering and curation strategies that support reporting, analytics, and AI/NLP use • At least two relevant technical certifications across data platforms, cloud, or analytics technologies. • Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience • An uncompromising commitment to quality, resilience, and regulatory compliance • Strong stakeholder engagement skills across business, technology, vendors, and leadership • Excellent problem-solving and decision-making capabilities • Ability to manage multiple concurrent initiatives under tight timelines • Clear and effective communication of technical concepts to non-technical audiences • Deep understanding of Agile and iterative delivery models • Proven ability to collaborate within globally distributed teams