Senior Manager, Data Product Manager

Visa•San Francisco, CA

2d•Hybrid

About The Position

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters — to you, to your community, and to the world. Progress starts with you. Job Description The Senior Manager, Data Product Manager role responsible for defining product strategy, direction, and outcomes for cross-domain initiatives within the Finance Data Platform. This role owns the product development lifecycle for platform-level data products from concept and prioritization through delivery and adoption while working in close partnership with Domain Data Product leaders, Data Architecture & Modeling, Data Governance, Engineering, and Program/Project Management. This role establishes the engagement model for how Finance partners with the Finance Data Platform and ensures product clarity, technical alignment, and AI-readiness across all initiatives.

Requirements

Basic Qualifications: 5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD
Experience: 8-12+ years in Data Product Management, Data Platform, or Finance Analytics roles.
Proven success operating as an individual driving cross-functional initiatives.
Demonstrated ownership of product development lifecycles for data or platform products.
Technical Skills: Strong hands-on expertise with Spark SQL.
Experience with Hadoop, Databricks, and Snowflake in enterprise environments.
Solid understanding of cloud data architectures (AWS preferred).
Familiarity with BI and analytics tooling (Tableau, Power BI).
AI & Advanced Analytics: Hands-on or product-level experience enabling AI/ML features in data products.
Leadership & Communication: Exceptional presentation and communication skills.
Ability to drive product strategy and alignment at Director and VP levels.
Strong decision-making, prioritization, and influence skills.

Nice To Haves

Preferred Qualifications: 6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
Familiarity with modern AI/ML platforms and GenAI tools as listed above.

Responsibilities

Product Strategy & Product Development Lifecycle: Own and drive the end-to-end Product Development Lifecycle (PDLC) for Finance Data Platform initiatives: discovery, definition, build, validation, and adoption.
Define product vision, value propositions, success metrics, and phased roadmaps for cross-domain data products.
Clearly articulate product scope, user stories, and acceptance criteria that reflect Finance business outcomes and technical standards.
Drive product strategy aligned to Finance priorities, platform maturity, and AI enablement goals.
Engagement Model Ownership: Define and operationalize the engagement model for how Finance teams interact with the Finance Data Platform (intake, prioritization, delivery, and adoption).
Serve as the primary point of coordination for cross-domain Finance initiatives that span Revenue, Expense, Deals, FP&A, Controllership, Tax, and Treasury.
Ensure Finance stakeholders understand what the platform delivers, how to engage, and what standards apply.
Partnership with Program / Project Management: Partner closely with Program and Project Managers by providing: clear product priorities and sequencing well-defined scope and acceptance criteria dependency context and decision clarity Participate in planning and alignment forums to ensure shared understanding of product intent.
Support program updates with product context and outcome-based narratives. This role does not manage delivery tracking or tooling but ensures delivery teams have strong product direction.
Director-Level & Cross-Domain Coordination: Work across Domain Data Product Directors to align shared initiatives and resolve cross-domain dependencies.
Partner with the Director – Finance Data Architecture & Modeling to ensure semantic consistency, canonical models, and interoperability.
Collaborate with the Director – Finance Data Governance to ensure all products meet governance, quality, and certification standards.
Technical Product Leadership: Engage deeply in technical design discussions and validate feasibility of product requirements.
Bring strong hands-on understanding of: Spark SQL Hadoop ecosystems (Hive, HDFS, Spark) Databricks (Delta Lake, Unity Catalog) Snowflake (performance optimization, data sharing) Ensure products are designed for scale, performance, auditability, and downstream analytics (Tableau, Power BI).
AI Enablement & Advanced Analytics: Drive AI-readiness of Finance data products through strong feature definition and data quality standards.
Leverage prior experience enabling AI/ML in products using tools such as: Databricks MLflow Databricks Feature Store AWS SageMaker Snowflake Cortex OpenAI / Azure OpenAI Vector databases (e.g., Pinecone, FAISS) Partner with Architecture and Governance leaders to ensure explainability, lineage, and responsible AI usage.
Translate AI capabilities into tangible Finance use cases (forecasting, anomaly detection, insights automation).
Executive Communication & Product Storytelling: Develop and deliver executive-ready presentations articulating: product strategy tradeoffs and sequencing progress and outcomes AI enablement value Influence senior Finance and Technology leaders through clear, structured storytelling.
Represent the Finance Data Platform in leadership forums with confidence and clarity.