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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Vice President, Data Modernization - Data Readiness & Metadata Standards - **Company:** JPMorgan Chase & Co. - **Location:** Wilmington, DE, United States - **Experience:** Expert - **Salary:** $133,000.0 - $205,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Big Data, Profiling, Data Governance, Data Transformation, Data Profiling, Python (Programming Language), Machine Learning, Meta-Data Management, Metadata Standards, Rapid Prototyping Process, SQL Databases, Unstructured Data, Scripting, Information Technology, Data Analytics, Data Management - **Published:** October 15, 2026 - **Apply:** https://www.businessworkforce.com/job.asp?id=3448869789&tx=FK8986FFR&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * Bachelor's degree in a quantitative, scientific, or technical field (for example, Mathematics, Statistics, Computer Science, Engineering, or Economics), or equivalent practical experience. * Seven years of relevant experience in data science, data management, data governance, data quality, or analytics engineering, including setting standards and influencing across teams. * Deep knowledge of metadata management and data catalog tools, with emphasis on discoverability, lineage, and interpretability. * Hands-on experience with structured and unstructured data at scale, including profiling, cleansing, standardizing, and documenting large datasets on enterprise platforms or data products. * Strong command of data quality frameworks and the ability to diagnose, measure, and drive remediation of quality issues. * Understanding of ontology and semantic/context layers, and how consistent definitions improve reuse across analytics and artificial intelligence systems. * Solid Structured Query Language (SQL) skills and analytical problem-solving, including root-cause investigation across large data volumes. * A first-principles mindset that questions assumptions and ensures data makes sense in context, not just in aggregate. * Working knowledge of how conversational analytics, natural-language querying, and agentic AI consume data, and the data conditions they depend on. * Strong attention to detail and an uncompromising commitment to accuracy. * Proven experience collaborating across product, engineering, and business teams in a regulated environment, with clear written and verbal communication for senior stakeholders. Preferred qualifications, capabilities, and skills * Experience in consumer banking or another large-scale, high-volume data environment. * Exposure to building or governing semantic models and metrics layers for enterprise analytics. * Familiarity with data domain modeling and standardization across multiple business units. * Scripting or full-stack skills (for example, Python) that support data profiling, enrichment, and rapid prototyping. * Applied exposure to artificial intelligence, machine learning, and generative AI concepts from the perspective of a consumer of well-governed data. ## Description As a Vice President in the Data Modernization program within Consumer & Community Banking Data & Analytics, you will lead work that makes structured and unstructured data more discoverable, interpretable, and dependable. You will define practical metadata and data domain patterns-business, technical, and operational-that help teams find, understand, and trust data at scale. You will partner with data owners and engineers to identify quality and definition gaps, prioritize fixes, and convert one-off improvements into scalable standards. You will translate technical progress into clear narratives and measurable outcomes that support roadmap decisions and executive updates. You will operate as a hands-on standards leader: comfortable in detailed data conversations, credible with engineers, and effective with senior stakeholders. You will balance governance and speed-setting clear expectations while enabling teams to move faster through reusable patterns, scorecards, and prototypes. You will help create the conditions for high-quality analytics, conversational querying, and generative AI experiences by improving the "readiness" of data upstream., * Shape and drive adoption of the enterprise data readiness framework across Consumer & Community Banking business units. * Define and champion standards for business, technical, and operational metadata so data is well-defined, discoverable, and trustworthy at scale. * Establish semantic and context standards that improve the consistency, interpretability, and reuse of data across analytics and artificial intelligence systems. * Lead profiling of priority domains to surface definitional, lineage, and data-quality gaps, and partner with data owners to close them. * Convert one-off fixes into repeatable, scalable enrichment patterns and mentor others to apply them. * Advise data leaders and engineers on the quality and usability improvements that create the most value across large datasets. * Build and showcase prototypes that demonstrate improved data readiness for analytics and AI-assisted use cases, including conversational and agentic experiences. * Own readiness scorecards and key performance indicators, translating progress into inputs for maturity assessments, roadmap decisions, and executive updates.