Director - Data Science & Data Engineering(AI)

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. 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 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.