Vice President - AI-Native Data Products & Legacy Modernization

Intellect Design Arena Ltd

Noida, Uttar Pradesh, India

Shape the Future of AI-Native Data Modernization!

At Intellect Design Arena, we are looking for an accomplished technology leader to spearhead the evolution of AI-native data products, cloud data platforms, and enterprise data modernization.

This is an opportunity to shape the future of enterprise data transformation by turning complex legacy modernization challenges into intelligent, scalable, and repeatable product capabilities that deliver measurable business impact.

Function: Product Engineering, Data Platforms & AI

Industry: Banking, Financial Services and Enterprise Technology

Experience: 18–24+ years in Enterprise Technology, Product Architecture, Data Modernization, or Platform Engineering

Grade: Vice President

Role Overview

We are seeking an accomplished Vice President to lead the strategy, architecture, engineering, and market adoption of AI-native data products that modernize legacy enterprise data warehouses.

This executive will own the evolution of data modernization platforms, migration accelerators, cloud data architectures, and AI-enabled analytics capabilities. The mandate is to transform complex, project-driven legacy migrations into repeatable, scalable product capabilities that improve modernization efficiency, reduce delivery complexity, and enable trusted access to enterprise data.

The VP will partner with business leadership, product management, engineering, sales, and client executives to establish the product vision, technology roadmap, architecture standards, and execution priorities across enterprise data modernization initiatives.

Key Responsibilities

1. Product Strategy & Portfolio Leadership

Define the product vision and multi-year roadmap for AI-native data modernization platforms.
Drive the evolution of reusable migration accelerators, cloud data products, and intelligent analytics capabilities.
Align product investments with client needs, market opportunities, business outcomes, and commercial priorities.

2. Legacy Data Warehouse Modernization

Lead modernization strategies for legacy SQL Server, Oracle, and other enterprise data environments, transitioning to cloud platforms such as Snowflake.
Establish repeatable approaches for data discovery, dependency analysis, migration, reconciliation, validation, and controlled cutover.
Ensure modernization preserves critical business rules, data integrity, and downstream reporting requirements.

3. AI-Native Platform Innovation

Drive the integration of AI into data discovery, migration analysis, metadata interpretation, quality assessment, and natural-language analytics.
Guide the evolution of AI-powered capabilities such as Natural Language Query (NLQ), ensuring enterprise data access is secure, governed, and appropriately validated.
Establish evaluation criteria for AI accuracy, reliability, explainability, and operational suitability.

4. Architecture & Engineering Excellence

Own technology direction across Snowflake, AWS, Azure, SQL Server, Oracle, and relevant modern data platforms.
Establish architecture principles, reusable engineering patterns, automation standards, and quality controls.
Guide teams in building scalable, maintainable, secure, and operationally resilient products.

5. Client Transformation & Commercial Enablement

Engage with CIOs, CTOs, enterprise architects, and data leaders on modernization strategy and target-state architecture.
Lead strategic solutioning, technical presales, and executive-level client discussions.
Translate implementation experience into product improvements, reusable assets, and differentiated customer propositions.

6. Executive Leadership & Organizational Development

Lead multidisciplinary product, architecture, engineering, and data teams.
Build technical leadership capability, establish clear accountability, and strengthen cross-functional execution.
Partner with business leadership on portfolio priorities, investment decisions, delivery effectiveness, and growth opportunities.

Required Experience & Qualifications

18–24+ years of relevant technology experience, including substantial leadership in data platforms, enterprise architecture, or modernization.
Demonstrated experience leading complex enterprise data warehouse migrations and cloud transformation programs.
Strong understanding of Snowflake and cloud ecosystems such as AWS or Azure, alongside SQL Server, Oracle, and enterprise data architectures.
Experience building or evolving reusable products, migration accelerators, or enterprise technology platforms.
Practical understanding of AI-enabled analytics, natural-language query, and the governance requirements of enterprise AI.
Strong executive stakeholder management, commercial awareness, architecture judgement, and multidisciplinary team leadership.
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field; postgraduate qualifications and relevant technical certifications are desirable.

Success Measures

Success in this role will be measured through:

Product Roadmap & Adoption: Execution of the product roadmap and adoption of reusable platform capabilities.
Modernization Efficiency: Improved migration repeatability, validation coverage, and delivery predictability.
Client Outcomes: Successful modernization outcomes across client environments.
AI-Enabled Business Value: Demonstrable quality and business value from AI-enabled data capabilities.
Engineering Excellence: Improved engineering productivity, architecture consistency, and platform scalability.
Commercial Impact: Strong client relationships, differentiated solution positioning, and contribution to business growth.

Expected Outcome

Establish a differentiated, AI-native data modernization portfolio that helps enterprises move from legacy warehouse environments to cloud-based, intelligent data platforms through repeatable engineering, trusted AI capabilities, and measurable client outcomes.

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