Lead Solutions Analyst - Data Catalog

Are you ready to lead at the intersection of data strategy, governance, and enterprise technology delivery? At JPMorgan

Chase, we believe that the right data - governed well, delivered reliably, and made accessible - is a competitive advantage. This is your opportunity to shape that future.

As a Lead Solutions Analyst at JPMorgan

Chase within the Corporate Data and Analytics Services team, you will play a pivotal role in advancing the firm's data strategy by designing and delivering enterprise-scale data solutions across the Corporate Technology organization. You will drive the execution of key data initiatives - including the Corporate Data Catalog, Data Lineage, Entitlements, and Data Quality frameworks - while collaborating with engineering teams, senior stakeholders, and Chief Data Officers to ensure high-quality, accessible, and reliable data assets.

Your work will directly support the firm's vision of a self-service, fully observable data platform that embraces data mesh and data product principles, enabling domain-driven ownership and consistent data management at scale.

• Lead end-to-end delivery of regulatory technology programs with regulator-reportable commitments, embedding control and evidence requirements into milestone exit criteria to ensure programs remain continuously audit-ready
• Own and operate a single intake and prioritization model across multiple competing senior stakeholder organizations, converting ad-hoc demand into a published, predictable roadmap with accountable delivery cadence
• Drive on-time milestone delivery against committed dates by managing agile delivery rhythms with engineering teams and proactively resolving cross-team dependencies and delivery risks
• Influence and secure engineering capacity and resources from teams outside direct reporting lines, negotiating scope trade-offs directly with Chief Data Officers and senior leadership
• Apply deep expertise in metadata management, data lineage, data governance lifecycle, data contracts, data tiering, and industry catalog standards to shape platform direction and ensure alignment with firmwide standards
• Instrument and analyze platform usage signals to diagnose adoption blockers, re-sequence roadmaps in response, and drive measurable enterprise-scale adoption through roadshows, enablement sessions, and self-serve onboarding materials
• Own the executive narrative for a multi-stakeholder platform, running senior governance forums and reporting milestone and risk status to senior leadership and regulatory and audit stakeholders
• Partner with engineering leads on sprint planning and backlog refinement to ensure roadmap commitments are reflected in sprint scope and delivery risks are resolved proactively
• Advance the firm's data mesh and data product strategy by fostering domain-driven data ownership, enabling self-service data platforms, and treating data as a product to ensure quality and reliability

• Formal training or certification on solutions analysis concepts and 5+ years applied experience
• Proven track record delivering technology programs with regulatory reporting obligations, including embedding audit-ready controls and evidence requirements into program delivery frameworks
• Demonstrated experience running a structured demand intake and prioritization model across multiple senior stakeholder organizations, with accountability for end-to-end agile delivery
• Experience influencing at the Managing Director level and above, securing resources from teams outside direct reporting lines and negotiating scope trade-offs with senior data leadership
• Deep working knowledge of metadata management, data lineage, data governance lifecycle, data contracts, and industry catalog standards such as DCAT and DPROD
• Proven ability to drive measurable platform adoption at enterprise scale, including diagnosing adoption blockers and leading enablement programs for technical and executive audiences
• Strong executive communication skills with experience owning governance reporting, running senior forums, and framing complex trade-offs for leadership decision-making

• Experience with AI-ready data product enablement and familiarity with data mesh principles and domain-driven data ownership models
• Familiarity with regulatory frameworks such as BCBS 239 or equivalent regulator-reportable data governance standards
• Experience collaborating with engineering teams on sprint…