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.
• Design end-to-end business and technology solutions that address complex customer challenges.
• Lead architecture reviews, solution blueprints, transformation roadmaps, and implementation strategies.
• Provide guidance on enterprise architecture, cloud modernization, AI adoption, and digital transformation programs.
• Ensure solution scalability, performance, security, and compliance.

Pre-Sales & Business Development

• Partner with sales leadership to identify, qualify, and close strategic opportunities.
• Lead client discovery workshops, executive presentations, capability demonstrations, and solution discussions.
• Own RFP, RFI, RFQ responses, solution estimation, pricing strategies, and proposal development.
• Develop compelling value propositions, business cases, and ROI frameworks for clients.
• Build and maintain trusted relationships with C-level executives, business leaders, and technology stakeholders.
• Support strategic account growth and large transformation pursuits.

Leadership & Talent Development

• Build, mentor, and retain high-performing teams of Data Scientists, Data Engineers, AI Specialists, Architects, and Consultants.
• Establish a culture of innovation, collaboration, accountability, and continuous learning.
• Drive workforce planning, capability development, succession planning, and leadership grooming.
• Foster strong collaboration across delivery, sales, product, engineering, and business teams.

Required Qualifications

Education

• Bachelor’s degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Engineering, Mathematics, Statistics, or a related discipline.
• Master’s degree (MBA, M.Tech, MS, MCA, or equivalent) in Computer Science, Artificial Intelligenc…