Tech PM

Overview: Role Overview We are seeking an experienced Senior Technical Project Manager to join our AI & Data Practice. The individual will manage one or more programs and multi-disciplinary teams delivering projects across data engineering, data migration, platform modernization, visualization, data science, machine learning, and Generative AI. This role requires strong expertise in managing data lifecycle projects, excellent stakeholder engagement skills, and proven experience in delivering large-scale programs on hybrid and cloud platforms (preferably GCP). Responsibilities: Key Responsibilities 1. Program & Project Delivery - Lead the end-to-end delivery of AI & Data programs across hybrid and cloud environments. - Manage multiple teams (5–50 members) across data engineering, ML/AI, and visualization streams. - Ensure adherence to project timelines, budgets, and quality standards. 2. Stakeholder Management - Serve as the primary point of contact for customers, ensuring clear communication and alignment. - Work closely with business sponsors, product owners, and technical leads to define scope, outcomes, and priorities. - Build strong relationships with customer stakeholders and executive sponsors. 3. Solution Oversight - Oversee design, migration, and implementation of solutions across data pipelines, platforms, and ML/AI models. - Guide decisions on modernization, refactoring, and cloud adoption strategies. - Support solution architects and technical leads in aligning delivery to business outcomes. 4. Financial & Governance Management - Own project financials, including budgeting, forecasting, and cost tracking. - Ensure compliance with delivery governance, risk management, and reporting standards. - Track and report on project KPIs, success metrics, and ROI. 5. Team Leadership - Lead distributed teams across engineering, data science, and platform operations. - Provide guidance, mentorship, and conflict resolution within project teams. - Foster a culture of accountability, innovation, and continuous improvement. 6. Cloud & Data Lifecycle Knowledge - Apply deep understanding of data lifecycle management, data science, ML/AI workflows, and Generative AI use cases. - Leverage experience with at least one major cloud platform (GCP preferred; AWS or Azure beneficial). - Stay current with evolving AI/ML and data technology trends to guide clients in adopting innovative solutions. ---------------------------------------- Required Qualifications Requirements: Required Qualifications - 12–15 years of IT experience, with at least 6–8 years in managing data and ML/AI lifecycle projects. - Proven experience in program/project management across data engineering, migration, cloud modernization, and advanced analytics initiatives. - Strong understanding of data lifecycle management, data science, machine learning, and emerging Generative AI applications. - Hands-on exposure to at least one cloud platform (GCP preferred; Azure/AWS beneficial). - Solid expertise in project financial management, governance, and reporting. - Strong background in Agile and hybrid delivery models. - Excellent communication, leadership, and stakeholder management skills. ---------------------------------------- Preferred Qualifications - Project Management certifications (PMP, PRINCE2, PMI-ACP, or equivalent). - Cloud certifications (Google Cloud Professional Data Engineer / Architect, AWS/Azure equivalents). - Experience working with global teams and large enterprise customers. - Prior experience in a Global System Integrator (GSI) environment is highly desirable.