Vice President Product Manager - Data Management

You enjoy shaping the future of product innovation as a core leader, driving value for customers, guiding successful launches, and exceeding expectations. Join our dynamic team and make a meaningful impact by delivering high-quality products that resonate with clients. Lead strategic initiatives to optimize operations and elevate customer experience through data insights and strong leadership

As a Vice President Product Manager - Data Management within the Consumer & Community Banking Data & Analytics team, you are an integral part of the team that innovates new product offerings and leads the end-to-end product life cycle. As a core leader, you are responsible for acting as the voice of the customer and developing profitable products that provide customer value. Utilizing your deep understanding of how to get a product off the ground, you guide the successful launch of products, gather crucial feedback, and ensure top-tier client experiences. With a strong commitment to scalability, resiliency, and stability, you collaborate closely with cross-functional teams to deliver high-quality products that exceed customer expectations. You will help lead Data State Intelligence (DSI) - a strategic intelligence layer that provides centralized, cross-platform visibility into data readiness, data state, data usage, cost transparency, and data quality across the Consumer & Community Banking data ecosystem.

Job responsibilities

• Develops a product strategy and product vision that delivers value to customers
• Manages discovery efforts and market research to uncover customer solutions and integrate them into the product roadmap
• Owns, maintains, and develops a product backlog that enables development to support the overall strategic roadmap and value proposition
• Builds the framework and tracks the product's key success metrics such as cost, feature and functionality, risk posture, and reliability
• Own the product roadmap, vision, execution, risk management, and performance outcomes for the platform. Manage the full product lifecycle by setting strategy, translating customer needs into prioritized capabilities, and continuously adapting the roadmap to deliver business outcomes. Coach and mentor product teams on best practices including solution generation, market research, storyboarding, prototyping, and product delivery.
• Be accountable for product performance by investing in enhancements and addressing barriers that limit adoption, usability, and operational scalability. Monitor market trends, conduct competitive analysis, and identify opportunities to differentiate through modern data observability, cloud-native data ecosystems, and cost intelligence practices.
• Define and drive strategic capabilities spanning data observability, cost transparency, data state tracking, usage analytics, and centralized metrics aggregation to deliver holistic data intelligence at scale. Lead development of core capabilities including data readiness observability, state-based lifecycle tracking, centralized alerting, cost attribution models, and AI-driven conversational experiences.
• Drive self-service intelligence experiences that enable stakeholders to proactively assess and act on data readiness, cost, and operational signals through unified dashboards and AI-driven conversational interfaces.
• Build AI-driven intuitive conversational experiences that enable users to explore data insights, ask questions in natural language, and act on intelligence through guided, interactive dialogue.
• Drive cross-platform integration by partnering with data platforms, pipeline infrastructure, and governance teams to ensure reliable metrics availability, consistent telemetry standards, and signal correlation.
• Connect data-state signals to customer, financial, and risk outcomes to drive business-impact intelligence and informed decision-making across the organization.

• 5+ years of experience or equivalent expertise in product management or a relevant domain area
• Advanced knowledge of the product development life cycle, design, and data analytics
• Proven ability to lead product life cycle activities including discovery, ideation, strategic development, requirements definition, and value management
• 5+ years of experience or equivalent expertise delivering products, projects, or technology applications. Extensive knowledge of the product development lifecycle, technical design, and data analytics
• Ability to drive adoption of product lifecycle activities including discovery, ideation, strategic development, requirements definition, and value management
• Experience driving change and managing stakeholders across multiple functions. Experience partnering with compliance, security, and governance stakeholders
• Executive-level product management capability within a large organization, including strong strategic thinking and crisp product communication
• Proven experience owning data observability, data intelligence, or similar cross-platform data products that aggregate signals across distributed systems. Strong grasp of data architecture principles including APIs, streaming, batch, lineage, data state modeling, and signal correlation patterns
• Deep understanding of multi-cloud data ecosystems, including platforms such as AWS, Databricks, and Snowflake
• Foundational understanding of AI/ML concepts including large language models, natural language processing, and conversational AI, with the ability to translate AI capabilities into user-centric product experiences
• Familiarity with design tools such as Figma and rapid prototyping techniques to effectively collaborate with design teams and iterate on product concepts

• Demonstrated prior experience working in a highly matrixed, complex organization
• Advanced degree in a related field (e.g., Computer Science, Business Administration)
• Familiarity with AI/ML integration for anomaly detection, intelligent alerting, and predictive data-state analytics
• Strong stakeholder management and executive communication skills, including experience presenting to C-level audiences
• Experience designing unified platform experiences that bridge technical depth and business accessibility and with modern data observability and intelligence platforms
• Familiarity with data state concepts, event-driven architectures, and near real-time data processing frameworks
• Experience defining responsible AI practices including managing bias, ensuring explainability, and addressing hallucination risks in AI-driven product experiences
• Familiarity with prompt engineering, conversational design patterns, and feedback-loop mechanisms for continuously improving AI-powered features