Delivery Head-Data Engineering

GenAI Strategy & Innovation

• Define and execute the enterprise GenAI vision, roadmap, and strategy in alignment with business objectives.
• Identify, evaluate, and prioritize GenAI use cases across functions, ensuring measurable ROI and business impact.
• Build and mature a centralized GenAI platform including LLM onboarding, vector databases, agentic frameworks, guardrail systems, and secure service layers.
• Lead the development of GenAI-powered products, copilots, automation tools, chatbots, and enterprise workbenches.
• Drive continuous enhancement of GenAI models, frameworks, and tools by exploring emerging technologies and industry trends.
• Evangelize GenAI adoption through demos, PoCs, education programs, and stakeholder engagement.
  

B. Data Engineering & Platform Modernization

• Lead large-scale data modernization initiatives, including migration from legacy systems to modern cloud-native data platforms.
• Architect and deliver scalable, secure, high-performance data ecosystems across ingestion, transformation, storage, and consumption layers.
• Build ingestion frameworks (batch/stream/CDC), integration pipelines, governance models, and self-service analytics capabilities.
• Oversee design and implementation of data lake/data mesh architectures using Snowflake, AWS, Azure, GCP, and related tools.
• Drive continuous optimization of performance, cost, TCO, observability, and data reliability.
  

C. Technology Leadership & Delivery

• Lead cross-functional engineering teams and vendor partners to deliver GenAI and data engineering programs end-to-end.
• Establish development standards, best practices, quality frameworks, and reusable architectural patterns.
• Guide teams on data modelling, pipeline orchestration, cloud-native engineering, and AI/ML operationalization.
• Ensure robust security, compliance, governance, and FinOps practices across the GenAI and data landscape.
• Manage project planning, WBS creation, execution tracking, and delivery on agreed milestones.
  

D. Cross-Functional Collaboration

• Work with CXOs, HODs, and business leaders to identify opportunities and translate requirements into technical solutions.
• Partner with product teams, technology teams, and business units to deploy GenAI and data-driven capabilities.