Project Data Manager

Role Summary

The Project Manager supports the Delivery Director in driving day-to-day execution of Data & AI initiatives. This role manages project planning, delivery tracking, cross-team coordination, governance routines, and customer communication. The PM ensures delivery predictability, manages risks and dependencies, supports capacity and financial tracking, and facilitates smooth collaboration across data engineering, platform, and analytics teams.

Location:

Key Responsibilities

1. Project Planning & Execution

• Own creation and maintenance of project plans, sprint schedules, milestones, and delivery roadmaps.
• Track execution across architects, tech leads, data engineers, platform teams, and QA.
• Ensure timely delivery of features, enhancements, and fixes.

2. Governance, Reporting & Compliance

• Run daily stand-ups, weekly status meetings, RAID reviews, and governance ceremonies.
• Provide transparent reporting on progress, risks, delays, and mitigation actions.
• Ensure documentation, approvals, and quality gates are adhered to.

3. Customer & Stakeholder Management

• Act as the first line of communication for customer teams for day-to-day delivery topics.
• Capture requirements, clarify scope, coordinate sign-offs, and manage expectations.
• Escalate issues to the Delivery Director when required.

4. Capacity, Resource & Work Management

• Support capacity planning, resource allocation, and workload balancing across teams.
• Help manage classification of BAU/transfer work vs transformation work.
• Track utilization, onboarding, rebadging transitions, and KT schedules where applicable.

5. Risk, Dependency & Issue Management

• Identify project risks early and drive timely mitigation.
• Coordinate dependencies across platform, data engineering, and analytics workstreams.
• Maintain RAID logs and ensure stakeholder alignment on key blockers.

6. Financial & Scope Tracking

• Track burn rates, effort consumption, and scope boundaries.
• Support the Delivery Director in forecasting and monthly financial reporting.
• Ensure changes are captured in CRs/SOWs where needed.

7. Automation & GenAI Awareness

• Identify areas where automation, workflows, agentic patterns, or GenAI can improve productivity.
• Work with engineering leads to track adoption and impact.
• Not expected to be a technical expert, but must understand automation opportunities.

Required Qualifications

• 10–15 years of IT experience with 5+ years in project management.
• Strong experience in data projects (data engineering, cloud, analytics, or platform programs).
• Excellent communication, planning, and stakeholder management skills.
• Hands-on experience with Jira, Confluence, MS Project, or similar tools.
• Understanding of cloud ecosystems (AWS/Azure/GCP) and platforms like Databricks (good to have).
• Exposure to GenAI/automation programs preferred.