Senior Project Manager - Investment Data

Senior Project Manager - Investments Data & Analytics

6-Months

Day Rate: $1050 - $1200

Melbourne or Sydney



Opportunity

· An opportunity has become available for an experienced Project Manager to join the Investments Data & Analytics function within one of Australia's leading financial services organisations.

· Working across a high-profile portfolio of investment technology initiatives, you'll lead the delivery of strategic data and platform projects that support investment operations, risk analytics and front-office decision making.

· The ideal candidate will have a strong understanding of investment management, data platforms and Agile project delivery, with the ability to confidently engage senior stakeholders across both business and technology.




Key Responsibilities

· Lead the end-to-end delivery of complex Investment Data and Analytics projects.

· Develop and manage project plans, milestones, budgets, RAID logs and governance artefacts.

· Partner with Investment business stakeholders to define scope, priorities and delivery outcomes.

· Coordinate cross-functional teams including Business Analysts, Data Engineers, Architects, Developers and QA.

· Manage dependencies across multiple workstreams and delivery teams.

· Drive Agile ceremonies including sprint planning, backlog refinement, showcases and retrospectives alongside Product Owners and Scrum teams.

· Identify and manage project risks, issues and delivery dependencies.




Experience

· Project Management experience within Investment Management, Asset Management, Superannuation or Wealth Management.

· Strong understanding of investment operations and investment data.

· Experience delivering projects involving investment platforms, performance data, risk analytics or portfolio reporting.

· Experience working with Agile delivery methodologies.

· Strong knowledge of Jira, Confluence and Agile delivery frameworks.




Highly Desirable

· Private Markets (Infrastructure, Property, Private Equity, Credit)

· Fund structures and investment operating models

· Risk Analytics platforms; FactSet, Bloomberg, Aladdin, SimCorp or similar investment platforms

· SQL or data analysis exposure (not hands-on, but sufficient to engage technical teams effectively)

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