Data Engineer Auditor at OUTsurance

Job Description

• The Data Engineer supports the Internal Audit function by providing independent assurance over the organisation's data landscape, including data infrastructure, data pipelines, data platforms, data quality controls, and data governance processes. The role focuses on assessing whether data is complete, accurate, reliable, secure, and appropriately governed as it moves across source systems, transformation layers, data warehouses, and reporting environments.
• The Data Engineer combines strong technical data engineering expertise with an assurance mindset to evaluate the design and operating effectiveness of controls across the data lifecycle. This includes reviewing data pipelines, ETL/ELT processes, infrastructure configurations, transformation logic, reconciliation controls, and data quality monitoring processes to provide assurance over critical business and reporting data.
• The role works closely with Internal Auditors, Data Engineering teams, Data Governance teams, IT, and business stakeholders to strengthen trust in organisational data and support the Internal Audit function's data-driven assurance strategy.
• The Data Engineer Auditor will also where required support the Internal Audit function by applying data analytics, automation, and data‑driven techniques to enhance audit coverage, efficiency, and assurance quality.  

Key Responsibilities

Data Infrastructure Assurance

• Provide independent assurance over the design, implementation, security, resilience, and availability of data platforms and infrastructure.
• Evaluate controls relating to cloud and on-premise data environments, including monitoring, deployment, change management, backup, and recovery processes.

Data Pipeline & Data Integrity Assurance

• Assess end-to-end data flows, pipelines, and transformation processes to ensure the completeness, accuracy, integrity, and traceability of data.
• Evaluate data movement, reconciliation, and lineage controls across source systems, data platforms, and reporting environments.

Data Quality & Governance

• Review the effectiveness of data quality controls, governance frameworks, standards, and ownership structures.
• Assess compliance with internal policies, regulatory requirements, and industry best practices relating to data management.

Data & Reporting Assurance

• Evaluate data models, business rules, and reporting datasets to ensure information used for operational, financial, regulatory, and analytical decision-making is reliable and fit for purpose.
• Validate the integrity of critical management and reporting information.

Audit Innovation & Continuous Assurance

• Develop and maintain automated audit testing, continuous auditing capabilities, and data-driven assurance solutions.
• Support Internal Audit's adoption of modern data engineering, analytics, and assurance techniques.

Data Engineering Standards & Advisory

• Contribute to the development of data engineering standards, frameworks, and best practices aligned with the OUTsurance Data Strategy.
• Provide assurance-related guidance to data and analytics teams on data quality, infrastructure, pipeline design, and governance practices.

Role Impact

The Data Engineer enables Internal Audit to:

• Provide assurance over critical data platforms and infrastructure.
• Assess the completeness and accuracy of data used for financial, operational, and regulatory reporting.
• Enhance confidence in organisational data assets.
• Identify risks within data pipelines and transformation processes before they impact business decisions.
• Support continuous auditing and data-driven assurance.
• Promote adoption of data engineering best practices aligned to the OUTsurance data strategy.
• Strengthen governance, quality, and trust across the Group's data ecosystem.

Qualifications
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.