Technical Project Manager

Technical Project Manager – Data & AIThe Technical Project Manager – Data & AI is responsible for planning, executing, and delivering medium to large-scale Data, Analytics, and AI projects within Professional Services or enterprise environments. This role acts as the bridge between business stakeholders and technical delivery teams, ensuring projects are delivered on time, within scope, budget, and quality standards.The role requires strong technical understanding of Data & AI ecosystems, experience working closely with engineers and data scientists, and the ability to translate business requirements into executable delivery plans. While not expected to be hands-on in development, the role demands deep delivery ownership and day-to-day project execution leadership.Role PositioningIndividual contributor project leadership roleNo direct people management responsibilityHands-on involvement in project planning, execution, and delivery trackingRequires technical depth across Data & AI domains, without coding responsibilitiesClient-facing role within Professional Services / Consulting / Internal Delivery teamsMandatory Profile Criteria4–10 years of experience in Technical Project Management or Delivery ManagementProven experience delivering Data, Analytics, and AI/ML projectsBackground in Professional Services, Consulting, System Integration, or Product DeliveryExperience working with cross-functional technical teams (Data Engineers, ML Engineers, BI Developers, Cloud Teams)Strong client and stakeholder communication skillsKey Responsibilities1. Project Delivery & ExecutionLead end-to-end delivery of Data & AI projects including Data Engineering, Analytics, BI, AI/ML, and MLOps initiatives.Own project planning, scope definition, timelines, dependencies, risk management, and execution tracking.Ensure delivery alignment with agreed architecture, quality standards, and business outcomes.2. Technical Project GovernanceDrive sprint planning, backlog management, milestone tracking, and delivery reviews across Agile or hybrid delivery models.Identify risks, issues, and dependencies early and drive mitigation plans with technical leads.Ensure adherence to data governance, security, and compliance requirements.3. Stakeholder & Client ManagementAct as the primary point of contact for clients or internal stakeholders for project-related communication.Translate complex technical concepts into clear, business-aligned updates for non-technical stakeholders.Manage expectations and ensure transparency on progress, risks, and changes.4. Collaboration with Technical TeamsWork closely with Data Engineers, Data Scientists, ML Engineers, Platform Engineers, and Architects.Support technical teams by removing blockers, clarifying requirements, and ensuring realistic commitments.Review technical plans, delivery approaches, and solution designs from a feasibility and risk perspective.5. Pre-Sales & Planning Support (as required)Support solution shaping, effort estimation, and delivery planning during pre-sales or project initiation phases.Contribute to identifying risks, assumptions, and dependencies during proposal or SOW creation.6. Delivery Excellence & Continuous ImprovementApply best practices in Agile, Scrum, or hybrid delivery frameworks.Capture lessons learned and contribute to continuous improvement of delivery processes and standards.Technical Knowledge ExpectationsStrong understanding of:Data Engineering & Data PipelinesCloud data platforms (Azure, AWS, or GCP)Analytics & BI solutionsAI/ML lifecycle and MLOps conceptsData governance, security, and privacy principlesAbility to engage confidently with architects and engineers on technical discussions without hands-on coding.Education & CertificationsBachelor’s degree (Engineering, Computer Science, or related field preferred)PMP / PRINCE2 / Agile or Scrum certification MandateCloud or Data-related certifications (Azure, AWS, Databricks, etc.) are a plusIdeal Candidate ProfileTechnically savvy project manager who enjoys working close to engineering teamsStrong organizer with excellent communication and stakeholder management skillsComfortable managing ambiguity in fast-paced Data & AI delivery environments