AI Finance Manager: Data & Governance Lead

EY; Phoenix (AZ); On-site; USD 143,000 - 285,000; Full time

Benefits offered by this job

Medical and dental coverage

401(k) plan

Paid time off

Job summary

EY is seeking an AI Finance Manager to support the Finance Applications Data Lead in defining and executing data management for finance tools. The role combines deep FP&A experience with mastery of enterprise data management, data governance, Data quality, and Gen AI to build a scalable FDL Blueprint and industry agnostic data model for finance applications.

You will collaborate with the Data Lead and Product Owner to ensure data architecture supports informed decision making, data consistency,

Qualifications

• Bachelor's degree required with 5+ years FP&A experience and strong finance data knowledge.
• Experience with planning, budgeting, forecasting, and financial modeling.
• Proficiency with enterprise performance management platforms (Anaplan, Oracle EPM, Hyperion, OneStream).
• Knowledge of data governance, data quality, and master data management for finance applications.

Responsibilities

• Lead design and delivery of system architecture solutions with technical teams.
• Tailor technology platforms to business processes to maximize value and ongoing improvements.
• Manage complex processes and projects with emphasis on quality and risk management.

Skills

EPM platforms

Anaplan

Oracle EPM Cloud

Oracle Hyperion

OneStream

Gen AI

Data governance

Finance data modeling

Education

Bachelor's degree in Finance, Accounting, Business, Computer Science

Tools

Azure

SQL

Job description

EY is seeking an AI Finance Manager to support the Finance Applications Data Lead in defining and executing data management for finance tools. The role combines deep FP&A experience with mastery of enterprise data management, data governance, Data quality, and Gen AI to build a scalable FDL Blueprint and industry agnostic data model for finance applications.

You will collaborate with the Data Lead and Product Owner to ensure data architecture supports informed decision making, data consistency,