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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Vice President, Data Owner Lead - Trust... - **Company:** JPMorgan Chase & Co. - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $128,250.0 - $205,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, User Authentication, Microsoft Azure, Big Data, Information Engineering, Data Governance, Data Systems, Data Warehousing, Fraud Prevention and Detection, Apache Hadoop, Scrum Methodology, Google Cloud, Cloud Platform System, Apache Spark, Data Lakes, Data Management - **Published:** July 18, 2026 - **Apply:** https://www.juju.com/job/00000000ghxv4b ## About the Role + Formal training or certification on data engineering concepts and 5+ years applied experience + 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 + 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 ## Description + Align data producers, consumers, and standards teams on data solutions that generate product insights and drive data modernization across the organization + Engage product owners on their roadmaps to surface related data enhancements and improvements needed by consumers of product data + Partner with analytics and modeling teams to identify the data needed to power product adoption and experience analysis, ensuring these needs are reflected in product release and data publishing plans + Lead discovery on new data modernization initiatives, including defining and refining business and customer value, and partnering with technology teams on feasibility and data availability + Refine and prioritize user stories, and lead sprint planning and execution - along with other agile ceremonies - for technology development teams supporting consumer experience requirements + Drive cross-functional alignment across stakeholders to communicate innovative data solutions effectively and oversee end-to-end deployment + Champion data governance and compliance practices that reduce data risk and ensure appropriate, responsible data usage across the team ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [The Missing Layer Between Enterprise Data and AI Agents](https://www.wearedevelopers.com/videos/100286-the-missing-layer-between-enterprise-data-and-ai-agents) - [Let's Get Aggregated: Custom UDAFs in Spark ](https://www.wearedevelopers.com/videos/1649-let-s-get-aggregated-custom-udafs-in-spark) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Got AI ideas but no money? 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