Project Manager/Scum Master
Project description
As part of the Development & Engineering section within the Information Technology Department (ITD), this role supports project and programme delivery, agile ways of working, and the continuous improvement of delivery processes. The initiative involves the development and management of in-house applications and data platforms, supporting projects from inception to acceptance while maintaining appropriate governance standards, delivery discipline, and industry good practices. Additionally, the project focuses on leveraging AI, automation, and AI agents to enhance operational delivery practices—such as automated reporting, action tracking, RAID management, backlog insights, and workflow automation across project and agile delivery practices
Responsibilities
- This person will be responsible for day-to-day project management and people management in the offshore delivery center. He/She will also be responsible for the delivery, scope, timeline, project status reporting, and other PM activities. Hands-on knowledge of software development methodologies is essential. Agile knowledge is a plus. Responsibilities will also include: * Scrum ceremonies * Negotiation with the customer and on-site Project Managers (delivery management, requirements management, requirements analysis etc.); * Introduction and enhancements of software development methodologies within the project; * Coordination and collaboration with other projects and QA engineers; * Change management process facilitation; * Team motivation, team building, assessment of project team members.
SKILLS
Must have
- A minimum of 4 years’ relevant experience in project management, scrum master, agile delivery, delivery coordination, or programme support roles
- Maintain a working understanding of tech delivery environments to engage effectively with engineering, data, architecture, security, and business teams.
- Experience with data and engineering concepts (cloud platforms, data platforms, DevOps, APIs, data pipelines, and SDLC).
- Utilize delivery and collaboration tools like Azure DevOps, Microsoft 365, Teams, SharePoint, and Power BI.
- Understand the purpose and delivery implications of technologies like Python, PySpark, SQL, Azure, AWS, and Databricks.
- Translate technical context into clear delivery plans, risks, dependencies, decisions, and stakeholder communications.
- Practical experience supporting technology, software, data, platform, or digital transformation initiatives
- Strong delivery discipline across scope, timeline, risk, dependency, quality, and governance management
- Excellent written and verbal communication skills, with the ability to translate complex delivery or technical topics into clear business language
- Excellent interpersonal, facilitation, negotiation, and stakeholder engagement skills
- Experience using delivery and collaboration tools such as Azure DevOps, Microsoft 365, Teams, SharePoint, Power BI, or similar platforms
- Working knowledge of technology delivery environments and concepts (cloud platforms, data platforms, DevOps, APIs, data pipelines, and SDLC) without requiring deep hands-on engineering ownership
- Ability to provide conflict resolution and support constructive decision-making across cross-functional teams
- Having strong planning, organizational, and follow-through skills with high attention to detail
Nice to have
• Bachelor’s or master’s degree in Computer Science, Engineering, Information Technology, Business, or a related discipline • Exposure to agile frameworks such as Scrum, Kanban, SAFe, or Product Owner practices • Practical awareness, curiosity, or exposure to AI, generative AI, Copilot, workflow automation, or AI-assisted delivery practices • Relevant professional training or certifications in project management, agile delivery, AI, or automation • Understanding of responsible AI, data protection, confidentiality, security, and governance considerations when applying AI-enabled solutions • Experience working alongside data engineering tools and cloud ecosystems (e.g., Python, PySpark, SQL, Azure, AWS, Databricks)
