Offres d'emploi

Shape the future of product delivery while crafting solutions that enhance and optimize customer experiences. Lead end-to-end processes, manage dependencies, and liaise with stakeholders as part of a team at the forefront of innovation.

As a Product Delivery Manager in the Data Products, Interactions Core team, you work to enhance and optimize the way products are delivered to customers. As a key member of the team, you create solutions and efficiencies that enable successful implementations in an expedient and organized way. You will lead the Sourcing & Data Streaming function focused on building connections to existing data streams and onboarding new data streams to Kafka and CCB Data Lake. You will partner closely with vendors, data owners, Product, Technology, and Subject Matter Experts across Chase to drive prioritization and execution in complex books of work to improve data availability & accessibility to accelerate AI/ML, modeling, personalization, reporting, and analytics use cases across the firm.

Are you a seasoned data leader passionate about building the real-time data foundations that power AI/ML, customer experience personalization, and enterprise analytics at scale? Join JPMorgan Chase in our Data Products, Interactions Core team, where you will drive high-impact data sourcing and streaming initiatives that unlock value across channels, products, and customer journeys. This is a leadership opportunity with room for growth to shape strategy, accelerate modernization of legacy data ecosystems, and deliver durable capabilities for the firm.

Job Responsibilities

• Leads end-to-end product delivery processes including intake, dependency management, release management, product operationalization, delivery feasibility decision-making, and product performance reporting, while escalating opportunities to improve efficiencies and functional coordination.
• Leads the completion of change management activities across functional partners and ensures adherence to the firm's risk, controls, compliance, and regulatory requirements.
• Effectively manages timelines and dependencies while monitoring blockers, ensuring adequate resourcing, and liaising with stakeholders and functional partners.
• Lead, mentor, and grow the Sourcing team, setting the vision, operating model, and measurable strategy for onboarding data sources to Kafka and CCB Data Lake.
• Build and maintain strong partnerships with vendors, data owners, Product, Technology, and SMEs across Chase, influencing prioritization and securing delivery commitments in teams where data sourcing is not a primary focus.
• Drive the strategy and execution to modernize legacy data sourcing by migrating high-value sources into real-time streaming via Kafka and ensuring reliable availability in CCB Data Lake.
• Partner with AI/ML, personalization, analytics, and reporting teams to understand use case requirements and translate them into a sequenced, outcome-driven data sourcing roadmap.
• Navigate complex organizational dynamics to align cross-functional teams on shared priorities, proactively managing dependencies, delivery risks, and stakeholder expectations.
• Establish and enforce data quality, governance, lineage, and documentation standards for newly onboarded data sources to ensure trust, auditability, and scalable reuse.
• Represent the Sourcing function to senior leadership, providing clear transparency on progress, risks, trade-offs, and value delivered, with a bias toward action and decision-ready communication.
• Foster a culture of accountability, technical excellence, and continuous improvement, raising the bar on execution rigor, stakeholder service, and operational resilience.

Required qualifications, capabilities and skills

• 5+ years of experience or equivalent expertise in product delivery or a relevant domain area.
• Demonstrated ability to execute operational management and change readiness activities.
• Strong understanding of delivery and a proven track record of implementing continuous improvement processes.
• Experience in product or platform-wide release management, in addition to deployment processes and strategies.
• Extensive experience in data engineering, data analytics or data product leadership roles, with a demonstrated track record leading and developing teams.
• Deep knowledge of streaming and batch data architectures, including Kafka and modern data lake platforms, with practical experience delivering production-grade ingestion patterns.
• Proficiency with SQL and a strong understanding of SQL database concepts.
• Strong understanding of data ingestion, transformation, and consumption patterns that support analytics, personalization, and machine learning use cases.
• Demonstrated success leading onboarding or integration of data from legacy systems into modern streaming and/or cloud data platforms, including dependency and migration management.
• Excellent executive communication skills, with the ability to translate complex technical topics into clear implications, decisions, and outcomes for senior business and technology stakeholders.
• Ability to manage multiple priorities and complex initiatives simultaneously, maintaining delivery momentum while addressing operational risks and stakeholder needs.

Preferred qualifications, capabilities and skills

• Bachelor's or advanced degree in Computer Science, Information Technology, Information Systems, Data Modeling, Engineering, or a related field.
• Significant large financial institution experience, with demonstrated ability to navigate legacy systems, cross-line-of-business data ecosystems, and complex governance landscapes.
• Familiarity with Data Lakes, streaming real time data with Kafka, and best practice data principles.
• Familiarity with major cloud platforms such as AWS and Snowflake.
• Experience enabling AI/ML and real-time personalization use cases through upstream data sourcing, including event design, data contracts, and operational monitoring.
• Strong knowledge of product development lifecycle and Agile delivery methodologies, with experience driving execution across multiple teams and dependencies.