Director – Data Science & Data Engineering(AI)

Position Summary

We are seeking an accomplished and visionary Director – Data Science, Data Engineering, AI Solutions & Pre-Sales to lead our AI and Data practice, drive strategic growth, and deliver transformative solutions for global clients. This role combines executive leadership, solution architecture, business development, pre-sales consulting, and delivery oversight across Data Engineering, Data Science, Artificial Intelligence, Generative AI, Analytics, and Cloud platforms.

The ideal candidate will have a strong blend of technical depth, consulting expertise, client-facing leadership, and business acumen, with a proven ability to build high-performing teams, win strategic opportunities, and deliver measurable business outcomes through data-driven innovation.

Location: Hyderabad,India

Key Responsibilities

Strategic Leadership & Practice Growth

• Define and execute the organization's Data, Analytics, AI, and Generative AI strategy aligned with business objectives.
• Build and scale a high-performing Data & AI practice, including Data Engineering, Data Science, AI/ML, GenAI, and Solution Architecture capabilities.
• Develop go-to-market strategies, solution offerings, accelerators, and industry-specific frameworks.
• Drive revenue growth, profitability, and market expansion for the Data & AI portfolio.
• Establish thought leadership through industry events, executive forums, whitepapers, and client engagements.

AI, Data Science & Analytics Leadership

• Lead the design, development, and deployment of advanced AI/ML, Generative AI, predictive analytics, NLP, recommendation engines, and intelligent automation solutions.
• Define AI adoption roadmaps and enterprise AI strategies for clients.
• Drive innovation using Large Language Models (LLMs), RAG architectures, Agentic AI, and AI governance frameworks.
• Ensure implementation of Responsible AI, model governance, and enterprise AI best practices.
• Oversee AI solution delivery from ideation through production deployment and value realization.

Data Engineering & Cloud Transformation

• Lead enterprise-scale data modernization and cloud transformation initiatives.
• Architect and implement scalable data platforms, data lakes, lakehouses, data warehouses, and real-time streaming solutions.
• Define enterprise data governance, security, metadata management, and data quality strategies.
• Drive adoption of modern cloud ecosystems and data platforms across AWS, Azure, and GCP.
• Establish DataOps and MLOps practices to improve operational efficiency and scalability.

Solution Architecture & Consulting

• Serve as executive sponsor and chief solution architect for strategic customer engagements.