Product Manager — Data Management

Product Manager — Data Management

As a Product Manager — Data Management within the Consumer & Community Banking Data & Analytics team, 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

• 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.

Required Qualifications, Capabilities, and Skills

• 10+ 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

Preferred Qualifications, Capabilities, and Skills

• 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