TELECOMMUTE Practice Head - Data Science and AI

We are looking for a seasoned Practice Lead - Data & AI to spearhead our global Data, Analytics, and Artificial Intelligence (AI) practice. The role combines technical leadership, strategic vision, presales engagement, and delivery excellence. You will be responsible for building and scaling data-driven and AI-powered solutions, defining the practice strategy, and driving customer success through Data Platforms, Analytics, and AI/GenAI and Agentic AU capabilities., Practice Leadership

• Establish and grow the Data & AI Practice, with true Sales enablement approach; covering Data Platforms, Data Lakes, Data Engineering, Analytics, AI/ML, Agentic AI and Generative AI.
• Define Strategic roadmap, accelerators, and reusable frameworks across data and AI adoption.
• Lead a team of Data Engineers, Analytics Consultants, AI Engineers, and Solution Architects, driving innovation and capability building.
• Build Centers of Excellence (CoE) for Data Platforms, Analytics, GenAI, Autonomous AI and responsible AI.
• Drive enterprise adoption of Modern Data Architectures (Data Lakes, Lakehouse, Data Warehouses).
• Work closely with global clients across North America, EU, APAC to design, deliver, and scale data-driven and AI-led solutions.

Client Engagement & Presales

• Partner with sales and account teams in presales, solution design and client presentations.
• Respond to RFPs/RFIs with integrated Data + AI solutions, influencing CXO-level stakeholders.
• Define data transformation strategies, analytics roadmaps and AI-led business Use cases.
• Enable data-driven decision-making frameworks for enterprise clients.
• Ensure solutions align with Data Governance, Data Quality, Responsible AI, compliance and security.

Strategic Initiatives

• Develop partnerships with leading Data Platform, Cloud and AI providers.
• Build thought leadership through whitepapers, accelerators and IP creation across Data & AI.
• Drive innovation in Data Lakes, Data Fabric, Data Mesh and AI-driven analytics ecosystems.
• Track and adopt emerging trends in Data Engineering, Analytics, Predictive Analytics, GenAI and Decision Intelligence., * Growth of Data & AI practice revenue and data-led transformation deals.
• Successful delivery of data platforms, analytics, and AI solutions with measurable business impact
• Establishment of data accelerators, reusable frameworks, and IPs.
• Improved data quality, governance maturity, and analytics adoption across clients.
• Team enablement through certifications, publications, and thought leadership.
• Strong references and repeat business from global enterprise clients.

• A strong customer-facing personality as this is essential for engaging clients and driving impactful conversations
• Excellent soft skills and presentation abilities to articulate complex solutions with clarity and confidence at an enterprise level
• We also need a thought leadership mindset, ensuring this role should shape solutions and guide strategic direction
• Sales enablement and a go-to-market approach (GTM) are truly critical with a clear focus on customer-centric strategies, * 14+ years of experience in Data Engineering, Data Platforms, Analytics and AI/ML.
• At least 5+ years in leadership / practice management roles.
• Strong expertise in Data Lakes, Data Warehousing and Data Transformation frameworks.
• Deep understanding of Data Governance, Data Quality, Master Data Management (MDM) and data compliance.
• Experience in Analytics, BI, and Predictive Analytics for business decision-making.
• Hands-on exposure to AI/ML, Generative AI, LLMs and Conversational AI.
• Strong knowledge of Data Engineering and Cloud-native platforms (AWS, Azure, Google Cloud Platform).
• Experience with modern data architectures (Lakehouse, Data Fabric, Data Mesh).
• Proven ability to engage clients, lead presales and influence CXO stakeholders.
• Proven track record of delivering large-scale data transformation and AI programs for global clients.
• Excellent leadership, communication and stakeholder management skills.

Preferred Qualifications

• Master/Bachelor in Computer Science, Data Engineering, Information Systems, or related fields.
• Certifications in Cloud Data Platforms (AWS, Azure, Google Cloud Platform) or AI/ML.
• Experience in building data accelerators, analytics frameworks, and GenAI solutions.
• Exposure to industry-specific Data & AI use cases (BFSI, Retail, Healthcare, Manufacturing, etc.).