Senior Project Manager - Group Data (f/m/d)

In this role you drive the strategic transformation of data as a business asset within Deutsche Börse Group. You work with the Chief Data Officer and senior stakeholders to scale data capabilities across eight businesses, shaping the data & AI strategy and governance. You lead cross-functional initiatives, manage complex programs, and partner with tech and business teams to enable data-driven decision making at scale. You will be a catalyst for a federated data culture and modern data platforms.

• Lead strategic data transformation initiatives across the Group and strengthen data capabilities like data products, data quality, and metadata management
• Drive adoption of data mesh principles and modern data governance across multiple business units and central functions
• Contribute to enterprise data & AI strategy and ensure data/context is fit-for-purpose for internal and external consumption
• Collaborate with business, product IT and shared IT teams to implement standards and scalable data platforms
• Manage project progress, milestones, KPIs, risks, and stakeholder communications; provide regular updates to senior management

• At least 5 years of digital transformation experience in financial services (bank, asset manager, hedge fund, trading firm, exchange, strategy/tech consultancy) with proven data & AI project leadership
• Master's degree in business administration, economics, IT, data science, engineering or related field
• Strong knowledge of data management, data products, data contracts, data quality, metadata, data distribution, and modern data architectures (data mesh, data fabric)
• Experience with enterprise data strategy, federated governance, and data target operating models
• Ability to lead interdisciplinary teams across business, product and IT and manage multiple jurisdictions and functions
• Project management expertise, ideally with PMP or PRINCE2 certification

• Strong communication across technical and non-technical audiences
• Change management and adaptability under pressure
• Collaborative mindset and team orientation
• Data mesh / data fabric
• Data governance and data quality
• Metadata management