Data Owner Lead, Vice President - Connected Commerce

About the role

Shape the future of data-driven decision-making at one of the world's most innovative financial institutions, where your expertise will directly influence how millions of customers experience trust, security, and seamless digital interactions. At JPMorganChase, we invest in our people and technology to build solutions that matter and we want you to be part of that journey.

Job Responsibilities

• Implement strategic plans to deliver data solutions and data products that support business operations and strategic objectives.
• Use SQL and data tooling to perform data testing and validation (e.g., completeness, accuracy, timeliness, reconciliation, anomaly detection), investigating variances and documenting test results to ensure ongoing data accuracy and integrity across curated datasets and data products.
• Document requirements for data sourcing, content, and quality. Define requirements for integrating multiple upstream sources (including mapping, transformation logic, and reconciliation) and for building curated datasets that support analytics and reporting use cases.
• Collaborate with partners to document and classify critical data with metadata. Ensure metadata is actionable and supports discovery and reuse (business definitions, technical metadata, lineage, quality rules/thresholds, and product documentation).
• Provide subject matter expertise on data content and usage within the business and associated product areas. Develop relationships with data providers and consumers across multiple functions. Engage broad-based consumer populations to understand usage patterns and improve usability of curated datasets and data products.
• Develop processes to identify and mitigate data risks throughout the data lifecycle, including data protection, privacy, retention, destruction, storage, use, and quality. Ensure controls are operationalized within pipelines and data products (e.g., automated quality checks, monitoring/alerting, and auditable evidence).
• Support data analytics by governing data integration into analytics platforms, including designing fit-for-purpose curated datasets and feature-ready data products for advanced analytics/ML use cases.
• Communicate and resolve data issues, maintaining data integrity; Support data issue triage and root-cause analysis with business and technology partners; drive remediation and preventative controls to reduce recurrence.
• Leverage AI/ML and LLM tooling to automate governance and data management activities (e.g., metadata drafting/classification, control evidence generation, quality rule suggestions, lineage/documentation assistance), including prompt creation and evaluation; contribute to agent-based workflow designs where appropriate.

Required Qualifications, Capabilities, And Skills

• Formal training or certification on data engineering concepts and 5+ years applied experience
• Advanced SQL proficiency (complex joins, window functions, CTEs) for data exploration, profiling, reconciliation, and root-cause analysis across large datasets.
• Hands-on data testing experience designing and executing validation frameworks with documented pass/fail criteria and evidence.
• 5+ years of experience in data management or data governance, including hands-on work with cloud platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure, and big data technologies such as Hadoop or Spark.
• Experience developing roadmaps and cloud platform-based solutions for data lake, data warehouse, and business intelligence dashboard environments.
• Demonstrated examples of leading data publishing initiatives that improved business insights while maintaining or strengthening data standards and controls.
• Proven track record of applying data governance and compliance methods to reduce data risk and ensure appropriate data usage.
• Exceptional ability to identify and reconcile stakeholder needs, drive innovative solutions, and communicate them clearly and confidently — both verbally and in writing — across cross-functional teams.
• Experience applying agile practices and partnering directly with technology scrum teams to translate product requirements and user stories into technical sizing estimates and delivery plans.
• Bachelor's degree in Science, Data, or a related field.

Preferred qualifications, capabilities, and skills

• Knowledge of business intent and customer experience goals for consumer banking products, particularly in areas such as Card, Payments, Identity, Authentication, or Fraud Prevention.
• Experience building automated data quality checks within pipelines (pre/post-load validations, monitoring/alerting, exception workflows) to prevent regression and support auditability.
• Familiarity with identity and trust frameworks or technologies.
• Experience working within large-scale financial services or highly regulated environments.
• Exposure to artificial intelligence and machine learning use cases in a data ownership or data governance capacit.