Senior Manager, Finance Data Governance

Okta Okta · Enterprise · San Francisco, CA · Accounting Operations-121

Senior Manager, Finance Data Governance at Okta, responsible for architecting trust and data integrity for the Finance organization. This role bridges AI innovation with financial compliance, focusing on policy creation, administration, execution, and leadership of the Finance Data Governance Council. Key responsibilities include implementing enterprise data governance standards, drafting AI-specific policies for transparency and bias mitigation, defining data lineage, managing metadata, and ensuring compliance with regulations like SOX, GDPR, and the EU AI Act. The goal is to transform data governance into a competitive advantage that accelerates AI adoption and executive decision-making.

What you'd actually do

  1. Provide strategic direction, oversight, and accountability for the Finance organization's data governance efforts.
  2. Implement enterprise data governance standards within the Finance domain, defining Finance-specific handling requirements, use case guidance, and operational procedures that extend corporate policies. This includes policies for data classification, retention, privacy, plus AI-specific policies (transparency, bias mitigation, and “hallucination” detection).
  3. Operationalize data policies into daily workflows in Finance and upstream at point of entry, ensuring that automated systems and manual entries adhere to established standards.
  4. Administer the FDGC program: coordinate meeting logistics, own agendas, facilitate discussions, and execute council decisions. The Council itself comprises VP-level Finance leaders who provide strategic direction and resolve escalated issues.
  5. Ensure data governance requirements are embedded throughout the model development and deployment lifecycles, including data quality validation, provenance tracking, and bias assessment.

Skills

Required

  • Data governance principles and frameworks
  • Financial data management
  • Policy creation and implementation
  • Cross-functional collaboration
  • Regulatory compliance (SOX, GDPR, EU AI Act)
  • Data quality management
  • Metadata management
  • Leadership and program management

Nice to have

  • Experience with AI/ML data governance
  • Familiarity with AI concepts (transparency, bias, hallucination)
  • Experience with dbt or SQL for data transformation
  • Experience with data lineage tools

What the JD emphasized

  • AI-specific policies
  • bias mitigation
  • hallucination detection
  • Ethical Use of AI in Finance
  • AI adoption
  • EU AI Act
  • AI regulations