Group Manager - Data Audit, AI & Digital Assurance Solutions

Job Purpose:

• The role holds accountability for defining data audit standards, methodologies, and continuous assurance approaches adopted by Group Internal Audit.
• Executes the risk-based Data Audit plan to provide independent assurance over the integrity, completeness, accuracy and consistency of critical data elements within DPWorld systems.
• Delivers Continuous Controls Assurance to provide timely assurance and actionable exception insights
• Builds and manage a portfolio of reusable audit analytics and audit accelerators that strengthen assurance, improve coverage and provide timely predictive risk intelligence to DP World leadership.
• Advances the digital transformation of Group Internal Audit (GIA) by embedding AI, automation, and data-driven methods across the entire audit lifecycle, maintaining effective processes for product innovation.
• Partners with Business Audit, Technology Audit, and Fraud Risk teams to co-create advanced digital solutions that enhance audit coverage and depth.
• Serves as the data governance and analytics assurance/AI subject matter expert, ensuring all solutions meet robust standards for quality, privacy, security aligned with IIA and leading data governance frameworks (i.e. DAMA).Key accountabilities:

Data Audit

• Lead the design and execution of standalone Data Quality Audits and integrated reviews. Evaluate the entire data lifecycle—from creation/ingestion to storage, usage, and reporting in a structured, end-to-end way ensuring alignment with industry standards and global policies.
• Assess the controls surrounding Critical Data Elements within key business processes. providing assurance on the integrity of data processed and feeding into operational dashboards, and AI/ML models.
• Maintain and continuously update the GIA Data Audit Methodology, defining specific testing procedures for data lineage, metadata management, and data quality dimensions (Accuracy, Completeness, Consistency, Timeliness, Validity).
• Maintain a dynamic Data Audit Universe that maps data assets to business risks, proactively identifying high-risk data silos or shadow IT that require assurance.Advanced Audit Analytics

• Deliver advanced analytics services that provide the GIA team with predictive insights into risks, governance gaps, and control effectiveness, enabling fact-based decision-making.
• Collaborate with Group IT and data owners to establish secure data pipelines and improve data lineage, ensuring data is reliable and accessible for audit consumption.
• Maintain strong controls over data handling and comply with information security and data protection requirements.
• Enforce rigorous standards for analytic workpapers, coding, and documentation. Oversee peer reviews to ensure all analytic solutions are auditable, repeatable, and fit for purpose.
• Develop and maintain a library of reusable scripts, tests, and visualizations aligned to common audit processes and risk objectives.Continuous Controls Assurance:

• Build and operationalise the Continuous Controls Assurance (CCA) framework for high-risk areas, establishing clear testing programs, exception management workflows, and escalation protocols.
• Integrate CCA outputs into dynamic risk assessments, providing real-time "always-on" assurance that allows GIA to pivot audit planning based on live risk triggers.Innovation & Digitalisation

• Identify opportunities to safely use automation/GenAI to streamline audit delivery while protecting confidentiality, independence and quality.
• Act as the internal audit thought leader on data trends, maintaining an external network to benchmark GIA against emerging technologies and identifying use cases for adoption.
• Stay current with emerging tools in machine learning and statistical modelling, identifying opportunities to upgrade the DADS tech stack and capabilities.
• Contribute to the overall process improvements within GIA through advanced analytics, automation, and AI.
• Stay current with emerging tools and techniques in machine learning, statistical modelling & analytics and identify opportunities to educate the GIA team and apply on DADAS work.Stakeholder Management:

• Build trusted relationships with stakeholders, translating technical data insights into clear, actionable business recommendations.
• Champion the use of advanced data visualization techniques (e.g., PowerBI) to present complex audit findings in an intuitive, high-impact manner
• Perform all assigned audit duties in manner that reflects the highest professional standards and complies with the guidelines of the Institute of Internal Auditors.
• Complies with Fatal Risk Standards, Health & Safety Policy and safe working practices, ensure responsibility for safety and discipline in work area and report accidents and ‘near misses’ in accordance with defined safety procedures.
• Able to understand business requirement and communicate effectively with business stakeholders.
Qualifications, skills and experience:

• University degree or Masters in the field of Computer Science, Data Science, Information Management, Data Analytics or equivalent
• Minimum of 8–10 years of professional experience with a specific focus on IT audit, data audit, and data governance.
• Experience in managing teams and delivering complex data projects.
• Hands-on experience auditing modern data architectures, specifically Databricks Lakehouse, Snowflake, or Azure Synapse. Must understand how to audit Data Lineage, access controls (Unity Catalog), and ETL/ELT pipeline integrity.
• Experience auditing complex data migrations (e.g., legacy to cloud) to ensure integrity and reconciliation.
• Proven track record of designing and implementing Continuous Controls Assurance (CCA) or Continuous Auditing frameworks.
• Experience in Data Governance, specifically with frameworks like DAMA-DMBOK, NIST, or ISO, and conducting data quality/lifecycle audits.
• Demonstrated experience in Advanced Analytics, utilizing AI/ML models to identify risks and anomalies in large datasets.
• Deep understanding of Data Engineering fundamentals (ETL/ELT). Must possess the technical literacy to supervise the end-to-end data acquisition process, from source identification to ingestion, ensuring that data transformation logic is rigorous, documented, and controls-compliant.
• Advanced understanding of SQL and Python/R sufficient to design, review, and challenge analytic solutions developed by the team
• Advanced ability to present large amounts of complex information using visualization techniques (e.g., PowerBI). Must be able to craft compelling narratives that drive executive action rather than just displaying data.
• Desirable Professional Certifications: CISA, CIA, CDMP, CGEIT, Databricks Certified Data Engineer/Analyst
• Proven ability to understand complex business requirements and translate them into technical data specifications. Capable of communicating effectively with non-technical stakeholders to bridge the gap between IT, Data, and Audit.
• Unwavering commitment to the highest professional standards, strictly adhering to the Institute of Internal Auditors (IIA) guidelines and internal Fatal Risk/H&S standards.
• Proactive approach to identifying avenues for improvement. A "change agent" who continuously scans the horizon for new tools (GenAI, Automation) to modernize legacy audit practices.