Data Owner Lead - Vice President

If you love turning messy, complex data into something teams can use, this role is for you. JPMorgan Wealth Management needs passionate Data Owners to deliver data strategies that bring the power of our data to life. You will sit at the intersection of Product, Technology, Analytics, and Risk & Controls to deliver data that unlocks business outcomes—without losing discipline on quality and protection.
As a VP Data Owner on the US Wealth Management Data & Analytics team, you will be responsible for end-to-end enablement, publishing, and governance for all data created and used by a single product. You set the “rules of the road” for product data—definitions, metadata, quality expectations, and controls—so it can reliably power analytics, AI/ML decisioning, and customer experiences. This role requires a unique blend of technical depth in data architecture and platforms combined with business acumen to drive clarity across providers and consumers, manage risk across the data lifecycle, and keep delivery moving through strong partnership and measurable outcomes.
Job Responsibilities
Own the product’s data agenda across creation, ingestion, publishing, and consumption by humans and AI models
Champion product data strategy in product forums and cross-functional working groups
Establish data quality requirements and monitoring for accuracy, completeness, timeliness, and lineage
Prioritize the delivery of data pipelines and products across multiple workstreams, ensuring dependencies and priorities are executed through Agile frameworks
Document business definitions, metadata, and classification so critical data is discoverable and understood
Maintain data governance standards, classification frameworks, and compliance controls for sensitive client and financial data
Manage data risks related to protection, retention/destruction, storage, and permitted use across the lifecycle
Investigate data issues, drive root cause analysis, and deliver remediation plans with clear ownership
Measure and communicate progress through KPIs and metrics that demonstrate data quality improvements and business value realization
Influence decisions at all levels of the organization with crisp communication, strong judgment, and a bias for execution
Required Qualifications, Capabilities and Skills
Bring 10+ years of experience in data delivery, analytics enablement, or data management
Demonstrate strong working knowledge of data management, data governance, big data platforms, and data architecture principles including dimensional modeling
Possess hands-on proficiency with SQL for data analysis, transformation, and quality validation across relational and big data platforms
Exhibit proven ability to prioritize effectively ambiguity in fast-paced environments with competing stakeholder demands
Communicate complex technical concepts clearly to both technical and non-technical audiences through documentation and presentations
Think analytically and systematically, breaking down complex problems into structured approaches with measurable outcomes
Understand Agile frameworks, participating actively in sprint planning, standups, and retrospectives with development teams
Collaborate effectively across organizational boundaries, building trusted relationships with diverse stakeholders and technical teams
Hold a Bachelor degree or equivalent experience
Preferred Qualifications, Capabilities and Skills
Bring experience from data science, analytics, or data engineering functions within financial services institutions or management consulting firms
Understand modern data architecture patterns including data mesh, data fabric, and domain-driven design principles
Demonstrate familiarity with field-based sales environments and CRM platforms such as Salesforce, particularly in wealth management or financial advisory contexts
Apply data governance frameworks, data ethics, and responsible AI considerations in regulated environments
Ability to profile, wrangle, and prepare data using advanced ETL tools and languages such as Python and SQL
Embrace a growth mindset and lifelong learning approach, staying current with emerging data technologies and industry best practices