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