Director – Data Science & Data Engineering(AI)

Position Summary

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 Intelligence, Data Science, Analytics, Engineering, Business Administration, or a related field is strongly preferred.
• Ph.D. in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Statistics, or a related discipline is highly desirable.

Professional Experience

• 18+ years of overall experience in Data Engineering, Data Science, Analytics, Artificial Intelligence, Cloud Technologies, or Digital Transformation.
• 8+ years of experience leading large-scale Data & AI practices, consulting organizations, or technology teams.
• Proven success in delivering enterprise-scale AI, analytics, and data transformation programs.
• Demonstrated experience managing P&L, practice growth, business development, and strategic client relationships.
• Strong experience supporting pre-sales, solution consulting, proposal development, and large deal pursuits.

Technical Expertise

• Machine Learning, Deep Learning, Predictive Analytics, and Statistical Modeling.
• Generative AI, Large Language Models (LLMs), RAG, Agentic AI, NLP, and AI Governance.
• Data Engineering, Data Warehousing, Data Lakes, Lakehouse Architectures, and Real-Time Data Platforms.
• Cloud Platforms: AWS, Microsoft Azure, and Google Cloud Platform (GCP).
• Big Data Technologies: Spark, Databricks, Hadoop Ecosystem, Kafka, and Distributed Computing.
• MLOps, DataOps, CI/CD, Model Monitoring, and AI Lifecycle Management.
• Enterprise Architecture, Solution Design, and Cloud-Native Application Architectures.

Leadership Competencies

• Strong executive presence with exceptional communication and presentation skills.
• Ability to influence senior stakeholders and C-level executives.
• Strategic thinking with strong business and commercial acumen.
• Proven people leadership, mentoring, and organizational development experience.
• Ability to lead global, cross-functional, and geographically distributed teams.

Preferred Certifications

• AWS Certified Solutions Architect – Professional
• Microsoft Certified: Azure Solutions Architect Expert
• Google Professional Cloud Architect
• Databricks Certified Data Engineer or Data Architect
• AI/ML Certifications from AWS, Azure, GCP, or equivalent
• TOGAF, SAFe, PMP, or Enterprise Architecture Certifications

Key Success Metrics

• Revenue growth and profitability of the Data & AI practice.
• Successful acquisition and closure of strategic opportunities.
• Client satisfaction, retention, and business expansion.
• Delivery of scalable AI and Data solutions with measurable business impact.
• Team growth, leadership development, and employee retention.
• Innovation, thought leadership, and market differentiation.