Director, Finance Data Platform – Data Modeling & Platform Features

Company Description

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 Director, Finance Data Platform – Data Modeling & Platform Features is responsible for leading the design, evolution, and adoption of enterprise finance data models and shared platform capabilities. This role focuses on building analytically rigorous, scalable data foundations that enable consistent reporting, advanced analytics, automation, and emerging AI use cases across Finance.

This leader operates at the intersection of Finance, Data Engineering, Analytics, and Enterprise Architecture, ensuring finance data is well‑modeled, governed, and technically enabled across modern cloud data platforms.

Key Responsibilities:

Finance Data Modeling Leadership

• Lead the design and governance of canonical finance data models, including GL, Expense, Cost Centers, Legal Entities, Accounting Periods, and enterprise hierarchies.
• Define and enforce dimensional and semantic modeling standards to ensure consistent metrics and analytical outputs.
• Translate accounting and finance requirements into scalable analytical data models implemented in cloud data platforms.
• Ensure strong alignment between source systems, data pipelines, modeled layers, and consumption tools.

Platform Features & Technical Enablement

• Own the product direction for shared finance data platform features, including:
  • Semantic layers and governed metrics
  • Data quality and reconciliation frameworks
  • Metadata, lineage, and documentation tooling
  • Standardized data access patterns for analytics and reporting
• Partner with Data Engineering to drive implementation using modern data platforms such as Databricks and Snowflake.
• Leverage SQL and analytical modeling techniques to validate models, troubleshoot issues, and guide technical design decisions.
• Enable advanced use cases including automation, predictive analytics, and AI‑assisted insights.

Cross‑Functional Leadership & Influence

• Act as a key connector across Controllership, FP&A, Accounting, Finance Operations, Data Engineering, BI, and Enterprise Architecture.
• Influence priorities and technical direction in a matrixed environment, balancing finance needs with platform scalability.
• Facilitate alignment on data definitions, metrics, and analytical standards across teams.
• Communicate complex technical and data concepts in clear, business‑focused language.

Controllership, Sourcing & Expense Analytics

• Partner with Controllership, Sourcing & Expense Data needs & analytics.
• Incorporate controllership requirements into platform standards without limiting analytical flexibility.

Governance, Quality & Analytics Adoption

• Establish standards for data quality, validation, ownership, and documentation.
• Ensure finance data assets are discoverable, trusted, and reusable.
• Drive adoption of BI and analytics tools by providing well‑modeled, performant datasets.

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager. 

Qualifications

Basic Qualifications:

• 10+ years of relevant work experience with a Bachelor’s Degree or at least 7 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 4 years of work experience with a PhD, OR 13+ years of relevant work experience.

Preferred Qualifications:

• 12 or more years of work experience with a Bachelor’s Degree or 8-10 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 6+ years of work experience with a PhD
• 10+ years of experience in finance data, analytics, or data platform roles, with 5+ years in leadership.
• Strong hands‑on expertise in finance data modeling and analytics, including dimensional modeling.
• Advanced proficiency in SQL for data analysis, validation, and modeling.
• Experience working with cloud data platforms such as Databricks and/or Snowflake.
• Experience enabling analytics through BI tools (e.g., Tableau, Power BI, Looker, or similar).