Data Project Manager

Data Project Manager (Data PM)

Important Information

Location: Singapore

12 months contract

Job Summary

We are seeking an experienced Data Project Manager (Data PM) to lead the successful delivery of data and analytics initiatives. The ideal candidate will manage end-to-end project execution, coordinate cross-functional data teams, and serve as the primary liaison between business stakeholders and technical teams. This role requires strong project management expertise, experience with Google Cloud Platform (GCP) data technologies, and a solid understanding of Generative AI, Agentic AI, and Large Language Model (LLM)-based solutions. The Data PM will be responsible for ensuring projects are delivered on time, within scope, and aligned with business objectives.

Roles & responsibilities

• Lead and manage end-to-end data projects, including planning, scope definition, resource allocation, execution, delivery, and project closure.
• Define project timelines, milestones, deliverables, and success criteria while ensuring adherence to budget and schedule.
• Perform effort estimation for data engineering, analytics, AI, and data platform initiatives, ensuring accurate project planning and resource utilization.
• Define technical scope in collaboration with architects, data engineers, and solution teams to ensure alignment with business objectives.
• Act as the primary point of contact between business stakeholders and technical teams, translating business requirements into scalable data solutions.
• Manage project risks, issues, dependencies, and scope changes while providing regular status updates to stakeholders and senior leadership.
• Lead and coordinate cross-functional data teams, including Data Engineers, Data Analysts, Data Scientists, ML Engineers, and Architects.
• Remove project blockers, facilitate technical discussions, and ensure timely decision-making to keep projects on track.
• Review technical designs, project deliverables, and solution approaches to ensure quality, scalability, and alignment with architectural standards.
• Drive Agile project delivery by facilitating sprint planning, backlog prioritization, stand-ups, retrospectives, and release planning.
• Collaborate with engineering teams to ensure successful implementation of data pipelines, analytics platforms, and AI/ML solutions on Google Cloud Platform (GCP).
• Support the adoption and delivery of Generative AI, Agentic AI, and LLM-based solutions by coordinating technical teams and business stakeholders.