Internal Audit Technology Enablement Lead
About the position The Internal Audit Technology Enablement Lead is responsible for driving the adoption and optimization of audit tools, automation, data analytics, and workflow solutions across the Internal Audit function to improve audit efficiency, consistency and quality. This role ensures audit platforms, analytics tools, and emerging technologies are purposefully designed, well-governed, and aligned with Internal Audit methodology, risk priorities, and long-term scalability. The position works in close partnership with Internal Audit leadership, audit teams, IT, and other stakeholders to strengthen audit execution through technology enablement, quality discipline and continuous improvement. Key responsibilities include ownership and continuous improvement of the AuditBoard platform, advancement of emerging technology and automation to enhance audit coverage and risk insight, and establishment of standards and repeatable approaches for audit analytics. In addition, the role leads key elements of the Quality Assurance and Improvement Program (QAIP), assessing adherence to Internal Audit methodology and evaluating engagement quality, documentation, and reporting consistency. QAIP insights are translated into actionable technology, process, and methodology enhancements, including updates to templates, systems, guidance, and ways of working, supporting consistent, high-quality audit execution across the function.
Responsibilities
- Lead Internal Audit’s use of AuditBoard as a strategic enablement platform, aligned to audit methodology, risk priorities, and enterprise governance expectations.
- Drive adoption of new AuditBoard capabilities, converting platform enhancements into tangible improvements across audit planning, execution, reporting, and insight.
- Design and evolve workflows, automation, and reporting within AuditBoard to improve audit efficiency, consistency, and visibility for management and the Audit Committee.
- Establish and maintain governance over access, configuration, and integrations, balancing usability, data protection, and effective coordination across the Enterprise.
- Lead Internal Audit’s exploration and responsible adoption of emerging technologies, including data analytics, automation, and AI, to strengthen risk identification, audit coverage, and insight.
- Identify, prioritize, and implement analytics and automation use cases that reduce manual effort, improve consistency, and enhance the quality and timeliness of audit results.
- Partner with audit leadership to embed technology-enabled procedures and analytics into the audit methodology and plan.
- Monitor evolving technologies and enterprise capabilities, translating relevant advancements into practical applications within audit processes, methodology, and audit scope.
- Lead QAIP review activities to assess adherence to Internal Audit methodology and ensure consistent, high‑quality execution, documentation, and reporting across all audit engagements.
- Evaluate engagement quality and procedural compliance, identifying thematic improvement opportunities and partnering with audit teams and leadership to strengthen methodology application and operational discipline.
- Translate QAIP insights into technology and process enhancements, recommending updates to templates, systems, and guidance and supporting the team in adopting improved practices.
Requirements
- 4-6 years of experience in Audit, Risk Management, or a related field.
- Bachelor’s degree in business, technical or a related discipline and/or commensurate experience.
- Certified Public Accountant (CPA)
- Certified Internal Auditor (CIA)
- Certified Information Systems Auditor (CISA)
- Certified Fraud Examiner (CFE)
- Chartered Property Casualty Underwriter (CPCU)
- Audit technology platforms and GRC systems (e.g., AuditBoard)
- Data analytics, visualization, and audit-relevant data modeling
- Workflow automation and process enablement
- Applied AI and emerging technologies in audit and assurance
- System configuration, integrations, and data governance
- Technology governance, model risk awareness, and responsible AI use
- Executive reporting and insight-driven analysis
- Business and risk acumen across audit, risk, and compliance functions
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