Lead Solutions Analyst, Data Catalog

What you'll do

• Lead end-to-end delivery of regulatory technology programs while embedding audit-ready controls into milestone exit criteria.
• Manage a single intake and prioritization model to convert stakeholder demand into a predictable, published roadmap.
• Drive on-time milestone delivery by managing agile rhythms and resolving cross-team dependencies with engineering teams.
• Secure engineering capacity and resources from outside reporting lines by negotiating scope trade-offs with senior leadership.
• Apply expertise in metadata management, data lineage, and governance standards to shape platform direction and firmwide alignment.
• Analyze platform usage signals to diagnose adoption blockers and drive enterprise-scale adoption through enablement sessions.
• Own the executive narrative by running senior governance forums and reporting risk status to regulatory and audit stakeholders.
• Partner with engineering leads on sprint planning and backlog refinement to ensure roadmap commitments are reflected in sprint scope.

What we're looking for

• Formal training or certification on solutions analysis concepts and 5+ years of applied experience.
• Proven track record delivering technology programs with regulatory reporting obligations and audit-ready controls.
• Demonstrated experience running a structured demand intake and prioritization model across multiple senior stakeholder organizations.
• Experience influencing Managing Directors and above to secure resources and negotiate scope trade-offs with senior data leadership.
• Deep working knowledge of metadata management, data lineage, data governance lifecycle, data contracts, and industry catalog standards.
• Proven ability to drive measurable platform adoption at enterprise scale and lead enablement programs for technical and executive audiences.
• Strong executive communication skills with experience owning governance reporting and running senior forums.
• Experience with AI-ready data product enablement and familiarity with data mesh principles (preferred).