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