Sr. Product Manager - Data Platform & Products

Visa•Bellevue, WA

1d•Hybrid

About The Position

The Visa Acceptance Platform team is seeking a Senior Product Manager to join the Acceptance Data Platform & Analytics organization. This team builds and operates a modern, cloud‑native data platform that enables Visa Acceptance products and domains to own, manage, and scale their data and analytics capabilities, while leveraging shared platform services for consistency, governance, and operational efficiency. The Acceptance Data Platform serves as the foundational layer for analytics, reporting, KPIs, and downstream intelligence across Acceptance products. While the platform increasingly supports AI‑enabled use cases, this role is first and foremost focused on data platform capabilities—including data ingestion, modeling, metrics standardization, APIs, governance, and analytics enablement at scale. We are looking for a Senior Product Manager with strong data platform and analytics expertise, who can partner deeply with data engineering and platform teams to deliver reliable, governed, and reusable data capabilities that power decision‑making across the Acceptance ecosystem.

Requirements

8 or more years of relevant work experience with a Bachelor Degree or at least 5 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 2 years of work experience with a PhD
Strong understanding of: Data modeling, schemas, and metrics design
Analytics and reporting platforms
How data quality and governance impact downstream use cases
Ability to partner effectively with senior data engineering and platform teams
Excellent communication, problem solving, and decision making skills in complex, ambiguous environments

Nice To Haves

9 or more years of relevant work experience with a Bachelor Degree or 7 or more relevant years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 3 or more years of experience with a PhD
Degree in Computer Science, Engineering, Information Systems, or a related field
Experience in Payment Processing domain
Proven experience owning and delivering complex data platform or analytics products
Hands on experience with cloud native data platforms (e.g., Amazon S3, Databricks, ClickHouse, or similar)
Familiarity with data mesh concepts, federated governance, or domain oriented data ownership
Experience building platform products consumed by multiple internal teams
Exposure to AI enabled analytics or ML use cases (as a consumer of data platforms, not as a core focus)

Responsibilities

Own the vision, strategy, and execution of the Acceptance Data Platform, ensuring it provides scalable, reliable, and well‑governed data foundations for analytics and reporting across Visa Acceptance products.
Work closely with data engineering, architecture, and analytics teams to define and prioritize cloud‑native data platform capabilities such as data ingestion, modeling, KPI and metrics standardization, APIs, and governance, while balancing domain flexibility with enterprise standards.
Enable consistent, trusted analytics and self‑service reporting for product teams, operational users, and leadership, and ensure the platform scales efficiently with strong performance and cost controls.
Ensure the data platform is AI‑ready by delivering high‑quality, well‑modeled data and standardized metrics that can be safely consumed by machine learning and AI platforms.
Drive cross‑functional delivery, measure success through adoption and data quality metrics, and continuously improve the platform based on telemetry and stakeholder feedback
Work closely with data engineering and platform teams to define and prioritize core data platform capabilities—such as ingestion, storage, data modeling, KPI standardization, APIs, and reporting frameworks—balancing scalability, performance, cost, and governance.
Translate complex platform and analytics needs into clear product requirements, maintaining a well‑prioritized backlog that engineering teams can execute against with confidence.
Review and validate data schemas, KPI definitions, and analytics designs to ensure metrics are consistent, reusable, and trusted across Acceptance products.
Partner with domain product teams and analytics consumers to understand how data is used today, identify gaps or duplication, and introduce shared platform capabilities that accelerate delivery and reduce fragmentation.
Guide the evolution of analytics and reporting experiences, ensuring dashboards, APIs, and self‑service tools are built on standardized data and platform‑defined metrics rather than one‑off implementations.
Collaborate with architecture, security, privacy, and governance teams to ensure data platform capabilities meet compliance, quality, and auditability requirements without slowing innovation.
Ensuring high‑quality, well‑modeled, and well‑governed data is available as input for models and AI workflows
Driving alignment between data platform capabilities and MLP/AIP requirements for feature consistency, reproducibility, and operational readiness
Partnering with ML and AI teams to identify platform improvements that simplify model training, deployment, and consumption—without shifting ownership of model logic into the data platform
Use platform telemetry, adoption metrics, and stakeholder feedback to continuously refine priorities and guide roadmap decisions.
Participate in agile delivery rituals to ensure predictable, high‑quality execution across multiple engineering teams.
Communicate platform progress, trade‑offs, and outcomes clearly to stakeholders and leadership, reinforcing trust in the data and analytics foundation.