Data Engineer

Job Description

The role of A&I is to provide independent, objective assurance and advisory services designed to protect and add value and improve the organisation's operations. A&I helps the organisation accomplish its objectives by bringing a systematic, disciplined approach to evaluating and improving the effectiveness of governance, risk management and control processes. The Data Engineer role in the A&I Digital Excellence team will design, build and operate reliable, secure data platforms and pipelines that power continuous auditing, predictive risk sensing, digital forensics, and analytics delivery for A&I/DEX
This role accelerates A&I’s shift toward data‑driven assurance, strengthens our ability to identify risks early, and ensures high‑quality, trustworthy data is available for auditors, investigators, and leadership.

Job Description Summary: -

The role of Audits and Investigation (A&I) is to provide independent, objective assurance and advisory services designed to protect and add value and improve the organization's operations. A&I helps the organization accomplish its objectives by bringing a systematic, disciplined approach to evaluating and improving the effectiveness of governance, risk management and control processes. The Data Engineer role in the A&I’s Digital Excellence team will design, build and operate reliable, secure data platforms and pipelines that power continuous auditing, Fraud pattern identification, continuous risk sensing, digital forensics, and analytics delivery for audits and investigation engagements.

This role accelerates A&I’s shift toward data-driven assurance, strengthens our ability to identify risks early, and ensures high-quality, trustworthy data is available for auditors, investigators, and leadership.

Job Description: -

Min 5+ years relevant experience in data engineering preferably in regulated or risk-focused environments. Experience supporting audit, investigation, compliance, or fraud-related data use cases, including evidence handling and defensibility.

Strategy & Stakeholder Management

· Collaborate with Data Scientists, Digital Forensics, Technology, investigation and audit teams to align data products to engagement needs.

· Partnering with auditors, investigators, data analyst and digital forensics specialists.

· Support governance tied to tech development and strategy (cataloguing, metadata, stewardship).

Tactical & Operational

· Develop scalable ETL/ELT workflows using Azure Data Factory, Synapse/Spark, Databricks, SQL, and Python.

· Creating well-structured, audit-ready datasets and curated layers for reuse across engagements.

· Implementing data quality controls, validation rules, lineage tracking, and transformation logic.

· Uphold privacy, access control, evidence integrity.

· Develop CI/CD, testing, observability and rollback for data services

· Support ML operationalization within A&I and explainability.

Teams & Capability Development

· Assist packaging of reusable components.

· Demonstrate reliable operations and incident response

· Participate in learning and experience transfer.

Ways of Working

· Uphold A&I/DEX methodologies

· Promote analytics and automation for digital auditing and investigations

· Drive adherence to data product SLAs/SLOs and continuous improvement.

· Operate in line with A&I independence and objectivity principles when designing and delivering data solutions.

· Effectively communicate technology, infrastructure, and deployment choices to both technical and non-technical stakeholders.

· Accountable for ensuring data products meet agreed quality, reliability, and audit/investigation‑readiness standards.

CORE SKILLS

· Experience building data products for analytics, ML and forensic workloads

· Strong proficiency in SQL, Python, Spark, and data orchestration (ADF/Airflow).

· Comfort with ambiguity and iterative delivery.

· Knowledge of data privacy, secure handling and auditability.

· Azure/Spark/Synapse/ADF, SQL, Python; strong grasp of batch & streaming architectures; schema design and optimization.

· CI/CD (GitHub/Azure DevOps), testing frameworks, observability (lineage, metrics, alerting), incident response.

· IAM, RBAC/ABAC, encryption, PII handling, auditability and evidence integrity; comfort in regulated environments.

· Strong data modelling skills (analytical and dimensional models) to support audit, investigation, and repeatable analytics use cases.

· Strong documentation skills covering data logic, transformations, assumptions, and limitations for audit transparency

Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.

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