Director - Data Science & Data Engineering(AI)

Position Summary\nWe 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.\nThe 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.\n\nLocation: Hyderabad,India\n\nKey Responsibilities\n\nStrategic Leadership & Practice Growth\nDefine and execute the organization's Data, Analytics, AI, and Generative AI strategy aligned with business objectives.\nBuild and scale a high-performing Data & AI practice, including Data Engineering, Data Science, AI/ML, GenAI, and Solution Architecture capabilities.\nDevelop go-to-market strategies, solution offerings, accelerators, and industry-specific frameworks.\nDrive revenue growth, profitability, and market expansion for the Data & AI portfolio.\nEstablish thought leadership through industry events, executive forums, whitepapers, and client engagements.\nAI, Data Science & Analytics Leadership\nLead the design, development, and deployment of advanced AI/ML, Generative AI, predictive analytics, NLP, recommendation engines, and intelligent automation solutions.\nDefine AI adoption roadmaps and enterprise AI strategies for clients.\nDrive innovation using Large Language Models (LLMs), RAG architectures, Agentic AI, and AI governance frameworks.\nEnsure implementation of Responsible AI, model governance, and enterprise AI best practices.\nOversee AI solution delivery from ideation through production deployment and value realization.\nData Engineering & Cloud Transformation\nLead enterprise-scale data modernization and cloud transformation initiatives.\nArchitect and implement scalable data platforms, data lakes, lakehouses, data warehouses, and real-time streaming solutions.\nDefine enterprise data governance, security, metadata management, and data quality strategies.\nDrive adoption of modern cloud ecosystems and data platforms across AWS, Azure, and GCP.\nEstablish DataOps and MLOps practices to improve operational efficiency and scalability.\nSolution Architecture & Consulting\nServe as executive sponsor and chief solution architect for strategic customer engagements.\nDesign end-to-end business and technology solutions that address complex customer challenges.\nLead architecture reviews, solution blueprints, transformation roadmaps, and implementation strategies.\nProvide guidance on enterprise architecture, cloud modernization, AI adoption, and digital transformation programs.\nEnsure solution scalability, performance, security, and compliance.\nPre-Sales & Business Development\nPartner with sales leadership to identify, qualify, and close strategic opportunities.\nLead client discovery workshops, executive presentations, capability demonstrations, and solution discussions.\nOwn RFP, RFI, RFQ responses, solution estimation, pricing strategies, and proposal development.\nDevelop compelling value propositions, business cases, and ROI frameworks for clients.\nBuild and maintain trusted relationships with C-level executives, business leaders, and technology stakeholders.\nSupport strategic account growth and large transformation pursuits.\nLeadership & Talent Development\nBuild, mentor, and retain high-performing teams of Data Scientists, Data Engineers, AI Specialists, Architects, and Consultants.\nEstablish a culture of innovation, collaboration, accountability, and continuous learning.\nDrive workforce planning, capability development, succession planning, and leadership grooming.\nFoster strong collaboration across delivery, sales, product, engineering, and business teams.\n\nRequired Qualifications\nEducation\nBachelor's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Engineering, Mathematics, Statistics, or a related discipline.\nMaster'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.\nPh.D. in Artificial Intelligence, Machine Learning, Data Science, Computer Science, Statistics, or a related discipline is highly desirable.\nProfessional Experience\n18+ years of overall experience in Data Engineering, Data Science, Analytics, Artificial Intelligence, Cloud Technologies, or Digital Transformation.\n8+ years of experience leading large-scale Data & AI practices, consulting organizations, or technology teams.\nProven success in delivering enterprise-scale AI, analytics, and data transformation programs.\nDemonstrated experience managing P&L, practice growth, business development, and strategic client relationships.\nStrong experience supporting pre-sales, solution consulting, proposal development, and large deal pursuits.\nTechnical Expertise\nMachine Learning, Deep Learning, Predictive Analytics, and Statistical Modeling.\nGenerative AI, Large Language Models (LLMs), RAG, Agentic AI, NLP, and AI Governance.\nData Engineering, Data Warehousing, Data Lakes, Lakehouse Architectures, and Real-Time Data Platforms.\nCloud Platforms: AWS, Microsoft Azure, and Google Cloud Platform (GCP).\nBig Data Technologies: Spark, Databricks, Hadoop Ecosystem, Kafka, and Distributed Computing.\nMLOps, DataOps, CI/CD, Model Monitoring, and AI Lifecycle Management.\nEnterprise Architecture, Solution Design, and Cloud-Native Application Architectures.\nLeadership Competencies\nStrong executive presence with exceptional communication and presentation skills.\nAbility to influence senior stakeholders and C-level executives.\nStrategic thinking with strong business and commercial acumen.\nProven people leadership, mentoring, and organizational development experience.\nAbility to lead global, cross-functional, and geographically distributed teams.\nPreferred Certifications\nAWS Certified Solutions Architect – Professional\nMicrosoft Certified: Azure Solutions Architect Expert\nGoogle Professional Cloud Architect\nDatabricks Certified Data Engineer or Data Architect\nAI/ML Certifications from AWS, Azure, GCP, or equivalent\nTOGAF, SAFe, PMP, or Enterprise Architecture Certifications\nKey Success Metrics\nRevenue growth and profitability of the Data & AI practice.\nSuccessful acquisition and closure of strategic opportunities.\nClient satisfaction, retention, and business expansion.\nDelivery of scalable AI and Data solutions with measurable business impact.\nTeam growth, leadership development, and employee retention.\nInnovation, thought leadership, and market differentiation.