Data Engineer Auditor

This role offers a unique opportunity for a technically proficient individual to bridge the gap between data engineering and internal audit, ensuring the integrity and reliability of an organisation's data assets. Based in Centurion, the position focuses on providing independent assurance over the entire data lifecycle. This involves scrutinising everything from the underlying data infrastructure and complex data pipelines to the data platforms themselves, as well as the effectiveness of data quality controls and overarching data governance processes. The core objective is to ascertain whether data is consistently complete, accurate, dependable, secure, and appropriately managed as it flows through various systems, including source systems, transformation layers, data warehouses, and reporting environments.

The Data Engineer Auditor will play a crucial role in bolstering trust in the organisation's data. This is achieved by meticulously evaluating the design and operational effectiveness of controls embedded within the data lifecycle. Key responsibilities will include:

• **Assessing Data Infrastructure:** Providing assurance over the design, implementation, security, resilience, and availability of both cloud and on-premise data platforms and infrastructure. This involves examining controls related to monitoring, deployment, change management, and backup and recovery procedures.
• **Ensuring Data Pipeline Integrity:** Evaluating end-to-end data flows, pipelines, and transformation processes to guarantee the completeness, accuracy, integrity, and traceability of data. This includes scrutinising controls for data movement, reconciliation, and lineage across diverse environments.
• **Reviewing Data Quality and Governance:** Examining the efficacy of data quality controls, the robustness of data governance frameworks, established standards, and defined ownership structures. A key aspect is assessing adherence to internal policies, regulatory mandates, and recognised industry best practices in data management.
• **Validating Data and Reporting:** Reviewing data models, business rules, and reporting datasets to ensure that information used for operational, financial, regulatory, and analytical decision-making is both reliable and fit for purpose. This extends to validating the integrity of critical management and reporting information.
• **Driving Audit Innovation:** Developing and maintaining automated audit testing capabilities, fostering continuous auditing practices, and creating data-driven assurance solutions. This role will actively support the Internal Audit function's adoption of modern data engineering, analytics, and assurance techniques to enhance coverage and efficiency.
• **Contributing to Standards and Advisory:** Participating in the development of data engineering standards, frameworks, and best practices that align with the organisation's strategic data vision. Additionally, providing assurance-related guidance to data and analytics teams on aspects of data quality, infrastructure, pipeline design, and governance.

What They're Looking For

To excel in this role, candidates should possess a strong foundation in data engineering combined with a keen assurance mindset. A Bachelor's degree in Computer Science, Engineering, or a closely related field is a prerequisite, complemented by 3-5 years of experience in data engineering, data platform engineering, or data architecture.

Essential technical and analytical skills include:

• Advanced SQL proficiency.
• A deep understanding of data engineering principles and architecture.
• Proven experience in designing and reviewing data pipelines and data platforms.
• Familiarity with data warehousing and dimensional modelling concepts.
• A solid grasp of data quality management and data governance principles.
• Experience with cloud-native data technologies.
• Knowledge of DevOps, infrastructure automation, and monitoring practices.
• The ability to independently assess data controls and identify risks that could compromise data integrity and reliability.
• Familiarity with key technologies such as Databricks, Airflow, Azure, Cosmos DB, Synapse, and Power BI is advantageous.

Beyond technical acumen, excellent written and verbal communication skills are vital, enabling clear articulation of findings and their significance to audit stakeholders. Strong organisational abilities to manage multiple tasks and priorities, coupled with high levels of drive and motivation, will be key to success.

This role is ideal for someone looking to leverage their technical data expertise within an assurance framework, contributing to robust data governance and building confidence in an organisation's data ecosystem. As an employer, they are committed to fostering an inclusive and diverse workplace and actively encourage applications from persons with disabilities and members of designated groups.

Academic Qualifications

• 3-5 years' experience in Data Engineering, Data Platform Engineering, Data Architecture, or related fields.
• Bachelor's degree in Computer Science, Engineering, or a related field
• Advanced SQL skills.
• Strong understanding of data engineering principles and architecture.
• Experience designing and reviewing data pipelines and data platforms.
• Experience with data warehousing and dimensional modelling.
• Strong understanding of data quality management and data governance.
• Experience with cloud-native data technologies.
• Understanding of DevOps, infrastructure automation, and monitoring practices.
• Ability to independently assess data controls and identify risks impacting data integrity and reliability.

Technical & Analytical Skills

• Understanding and knowledge of key technologies:
  • Cloud solutions (Databricks, Airflow, Azure, Cosmos DB)
  • Synapse/ Solid
  • SQL
  • PowerBI
• Experience with Data Governance.

Communication & Professional Skills

• Excellent written and verbal communication skills, with the ability to clearly explain what is relevant and important to audit stakeholders.
• Strong organisational skills with the ability to manage multiple tasks and priorities.
• High levels of drive and motivation, with a proactive approach to continuous improvement.
• Creativity and innovation in developing practical, data‑driven solutions to improve audit processes.

Key Attributes for Success in Internal Audit

• Assurance-focused mindset.
• Strong understanding of how data is created, transformed, stored, governed, and consumed.
• Ability to think end-to-end across the data lifecycle.
• Curiosity to investigate data anomalies and root causes.
• Strong documentation discipline and audit trail awareness.
• Ability to bridge technical data engineering concepts and Internal Audit assurance requirements.
• Strong attention to detail and professional scepticism.
• Ability to link data anomalies to audit risks and internal control implications.
• Methodical, well‑documented approach to ensure audit work is repeatable and defensible.
• Collaborative mindset with a service orientation toward the Internal Audit team.
• Ability to think “upstream” about how data is created, transformed, and governed, not only how it is analysed.