Data can accelerate growth only when it is trusted, well-defined, and protected. In this role, you will own how Small Business Deposits data is sourced, documented, delivered, and used to power decisions across the business. You will partner with product, technology, analytics, operations, and risk and control teams to strengthen data quality and reduce data risk. Your work will directly support faster product development and a better Chase customer experience. If you enjoy translating complex data into clear outcomes, this is a high-impact opportunity.

As a Data Owner in Small Business Data and Analytics, you will be accountable for the data used across the Small Business Deposits product to support business objectives, advanced analytics, operations, and reporting. You will define, classify, and publish critical data, ensuring assets are clearly documented, high quality, and appropriately protected. You will collaborate with business partners, technology teams, and third-party vendors to deliver data that meets quality and safety expectations. You will execute processes to identify, monitor, and mitigate data risks throughout the data life cycle in alignment with firmwide policies and standards.

Job responsibilities

• Participate in the planning for the development and delivery of Small Business data to support strategic business objectives, business operations, advanced analytics, and reporting
• Define critical product data scope with business partners and clarify how the data will be used
• Partnering with our Product Team members to ensure project requirements and acceptance criteria are fully identified and accurately captured in the associated EPICs
• Coordinate with third-party vendors to establish and maintain published data assets for the Small Business Deposits portfolio
• Support modernization of published assets into enterprise data lake and enterprise data warehouse environments
• Align with other data owners to obtain approvals and enable responsible use of shared data assets
• Resolve data delivery issues with data technology partners to keep assets on track and fit for use
• Document data assets at the column level, including names, definitions, data types, access controls, retention controls, and protection assignments
• Explain data meaning and usage as a subject matter expert across stakeholders and functions
• Build relationships with data consumers across business, technology, analytics, operations, risk, and control functions
• Lead direct or matrixed team members to execute data-related work and deliver outcomes

Required qualifications, capabilities, and skills

• Bachelor27s degree and 5+ years of industry experience in a data-related role
• Hands-on knowledge of data management and governance, data integration, data warehousing, business intelligence, and machine learning concepts
• Familiarity with public cloud data platforms (for example, Amazon Web Services)
• Ability to manage delivery across multiple workstreams with different timelines and dependencies
• Experience creating process flows, data flows, and business requirements documentation
• Demonstrated ability to deliver outcomes through strong internal partnerships
• Working knowledge of agile delivery practices, including Scrum-based development
• Ability to operate effectively in ambiguous environments while staying organized and driving progress
• Experience supporting risk and control requirements related to data quality, access, and protection
• Strong interpersonal and communication skills, including the ability to align stakeholders

Preferred qualifications, capabilities, and skills

• Master27s degree
• Domain knowledge in small business banking processes, products, or product data
• Practical experience in big data engineering, analytics, or machine learning solutions
• Experience with cloud-based data technologies and their business applications
• Knowledge of query or analytical programming languages used for data analysis
• Product life cycle experience, including product management partnership
• Understanding of extract, transform, and load principles and common data structures