Technical Project Manager – Marketing Measurement Platform

About the role

We are looking for a Technical Project Manager to lead the delivery of an enterprise‑wide marketing measurement and optimisation platform. The role will coordinate data science, engineering and MLOps teams, using agile practices to ensure timely, high‑quality releases.

Key responsibilities

• Lead Agile scrum ceremonies and manage workflows across Data Science, Data Engineering, App Engineering, and MLOps teams; maintain JIRA boards, tickets and backlog.
• Facilitate technical feasibility decisions and ensure delivery across model, pipeline and application layers, including validation and production readiness.
• Create and manage detailed timelines, roadmaps and identify dependencies and critical path items.
• Partner with internal Marketing, Analytics, Data & Technology teams and external vendors to align priorities and deliverables.
• Use tools such as JIRA, Confluence, SharePoint and roadmap software to track execution; work with Snowflake, AWS (S3, SageMaker), DBT pipelines and MLFlow.
• Maintain clear tracking of tasks, dependencies, risks and deliverables; document decisions in JIRA and Confluence.
• Own technical processes for model validation, retraining, pipeline updates and releases.
• Produce status updates and presentations for technical and business audiences and support onboarding of new stakeholders.

Required profile

• Bachelor’s degree in a relevant field and at least 5 years of project or program management experience.
• Proven experience leading complex data‑driven technology initiatives from inception to production.
• Strong background in Agile delivery, backlog management and sprint execution.
• Ability to solve cross‑functional problems, identify risks and drive resolution.
• Excellent communication skills for facilitating discussions with technical and executive stakeholders.

Required skills

• JIRA, Confluence, SharePoint, OneDrive, PowerPoint, Excel
• Snowflake data platform
• AWS services: S3 and SageMaker
• DBT for data transformation
• MLFlow for model tracking and deployment
• Experience with data pipelines, MLOps and model validation processes
• Agile and Scrum methodologies