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.

Strategy & Stakeholder Management

Collaborate with Data Scientists, Forensics, TSE, BI 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 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.

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

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.

We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com.

CORE SKILLS Data Integration and ETL (Extract, Transform, Load) practices: Combining data from different sources into a single, unified view, and the process of extracting data from sources, transforming it into a suitable format, and loading it into a destination system. Proficiency Level: Advanced Data Analysis: The process of inspecting, cleansing, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making Proficiency Level: Proficient Data Processing Frameworks: Tools and libraries used to process large data sets efficiently, such as Apache Hadoop and Apache Spark. Proficiency Level: Proficient Programming: Writing code to manipulate, analyze, and visualize data, often using languages like Python, R, and SQL. Proficiency Level: Proficient Data Modelling: The process of creating a data model for the data to be stored in a database, representing the data structures and their relationships. Proficiency Level: Proficient Data Quality Management: Ensuring that data is accurate, complete, reliable, and relevant for its intended use. Proficiency Level: Advanced SPECIALIZED SKILLS Data Management: The development and execution of architectures, policies, practices, and procedures to manage the data lifecycle needs of an enterprise. Big Data Technologies: Tools and techniques used to process and analyze large and complex data sets that traditional data-processing software cannot handle Database Design and Management: The process of designing, implementing, and maintaining a database system to ensure data is stored efficiently and securely. Data Visualization: The graphical representation of data to help people understand complex data sets and derive insights. Data Security: Protecting data from unauthorized access, use, disclosure, disruption, modification, or destruction. Data Storage solutions: Systems and technologies used to store data, such as databases, data warehouses, and cloud storage. Data Governance and Compliance: The management of data availability, usability, integrity, and security in an organization, based on internal data standards and policies. Ensuring that an organization adheres to external regulations and internal policies, managing risk, and maintaining ethical standards Technical Documentation: Creating and maintaining documentation that explains the functionality, use, and maintenance of software or systems. Data Architecture: The design and structure of data systems, ensuring that data is stored, managed, and utilized efficiently CI/CD & Observability: The use of continuous integration and continuous delivery (CI/CD) pipelines to automate the process of software development, including building, testing, and deploying code Definition of Proficiency Levels: Foundational: This is the entry level of the skill, typically expected when starting a new role or working with the skill for the first time. You rely on strong manager support, coaching, and training as you build the capability to progress to higher proficiency levels. Proficient: This is the level at which you are considered effective in the skill. You demonstrate more than just functional competence—you begin to have a noticeable impact in your role by applying the skill consistently and meaningfully. You require only minimal support, coaching, or training to apply the skill successfully. Advanced: This is the level where you move beyond meeting expectations to actively leading, influencing, and delivering considerable impact across the wider business. You are seen as a role model, demonstrate the skill independently, and require little to no manager support.