Job Description
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
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.
