Join NTT DATA, a global leader in business and technology services, and contribute to shaping innovative Data, AI, and GenAI initiatives. This role offers the chance to influence large-scale enterprise transformation programs and collaborate with industry leaders and global clients.

As a Sr. Advisor, Data Architect, you will be instrumental in transforming data into tangible business value and driving AI-powered outcomes for our clients. We seek passionate individuals eager to grow with a forward-thinking and inclusive organization.

Spearhead client discovery sessions and solution workshops, architecting comprehensive solutions across Data, Analytics, AI, GenAI, Governance, and Cloud modernization.

You will own the technical solutioning for RFPs, RFIs, and strategic pursuits, developing target-state architectures, transformation roadmaps, and compelling value cases.

Collaborate effectively with sales, consulting, delivery, and alliance teams to craft differentiated solutions. Responsibilities include building effort estimates, defining assumptions, identifying risks, and outlining implementation approaches, alongside presenting solutions to executive-level clients and stakeholders.

Develop reusable accelerators, reference architectures, and thought leadership assets, while also mentoring architects and contributing to practice growth.

This role is ideal for experienced Presales Solution Architects with a strong blend of business strategy acumen and technology execution expertise. A minimum of 10 years in Data & Analytics, Cloud, or AI is required.

Proven experience in solution architecture and presales is essential, coupled with robust client-facing and stakeholder management skills. Experience leading significant, multi-million-dollar transformation pursuits is highly valued.

Candidates should possess the ability to translate complex technological concepts into measurable business outcomes. Expertise in Enterprise Data Architecture, Data Engineering, Lakehouse Platforms (Databricks, Snowflake, Microsoft Fabric), cloud platforms (Azure, AWS, GCP), Data Governance, MDM, Data Quality, AI/GenAI, and Integration/API Architectures is critical.