Senior Manager, Finance Business Architect

Workday Workday · Enterprise · Pleasanton, CA

This role focuses on architecting the finance function to be AI-ready by establishing data quality, governance, and system integration foundations. It involves translating finance processes into scalable system and data designs, ensuring data integrity, and defining master data management standards to support AI and advanced analytics use cases within the finance organization.

What you'd actually do

  1. Partner with Business Technology on the Finance Technology roadmap, evaluating, rationalizing, and consolidating the tool landscape to reduce redundancy and improve efficiency.
  2. Serve as the Finance Business Architect, translating finance process requirements into scalable system and data designs.
  3. Lead the identification and resolution of data integrity and consistency issues across finance systems and data pipelines.
  4. Help design and implement a Finance Data Governance framework, including policies, ownership models, stewardship accountabilities, and escalation paths partnering with the data governance team within a workday.
  5. Build and maintain reconciliation and validation frameworks to ensure data accuracy and completeness.

Skills

Required

  • 12+ years of experience in finance technology, business architecture, data governance, or a related discipline, with progressive responsibility.
  • 5+ years of experience leading and developing high-performing teams.
  • Demonstrated understanding of core finance processes — close, consolidation, planning, reporting, and procurement-to-pay, Order-to-cash, FP&A.
  • Experience building anomaly detection frameworks within a finance context, including designing detection logic, defining thresholds, and operationalizing alerts to identify data inconsistencies, process exceptions, or financial irregularities.
  • Experience translating finance process requirements into scalable system and data designs, including mapping current-state and future-state processes

What the JD emphasized

  • AI-first finance function
  • data integrity
  • data quality and governance foundations
  • AI-ready
  • enable AI and advanced analytics use cases
  • anomaly detection frameworks