Data Owner Lead

Data Product Manager

Implement strategic plans to deliver data solutions and data products that support business operations and strategic objectives. Provide subject matter expertise with respect to the content and use of data in the product and associated business area. Identify the scope of critical data within their product, ensuring that the prioritized data is well-documented as to its meaning and purpose, and classified accordingly with metadata to enable its understanding and control. Support the aligned Data & Analytics lead for their product by identifying data required to be integrated into analytics platforms to support analytics projects and document requirements for the accuracy, completeness, and timeliness of data within the product, and coordinate resources to deliver data quality requirements. Partner with business & analytics stakeholders to define requirements for new data products and collaborate with data engineering teams to deploy production-ready solutions and develop processes and procedures to identify, monitor, and mitigate data risks for data in the product, including risks related to data protection, data retention and destruction, data storage, data use, and data quality. Manage the execution of tasks to comply with Firmwide policies, standards, and procedures related to the integrity and protection of data in the product and develop strong relationships with product data delivery partners and data consumers, including leaders in the Business, Technology, Analytics, Operations, Risk and Control functions and manage the execution of a set of milestones and understand and mitigate risks, bottlenecks, and inefficiencies in the product development lifecycle with respect to data. Track and manage workstreams and associated KPIs to ensure deliveries are successful. Manage direct or matrixed staff to execute specific data-related tasks. 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. 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.

6+ years of industry experience in a data-related field; Bachelor's degree required. Experience managing delivery across multiple workstreams with varying timelines. 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 plan.

Master's degree preferred. Knowledge of business intent and customer experience goals for consumer banking products, particularly in areas such as Debit Cards, ATM, 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 capacity. Experience building and deploying data products is preferred.