Master Data Governance Engineer

Responsible for the end-to-end analysis, configuration, development, testing, delivery, and support of SAP Master Data Governance solutions. The role combines SAP MDG functional expertise with hands-on ABAP development, with a primary focus on Finance Master Data and the ability to deliver assigned work within defined standards, methods, and priorities. SAP MDG provides change-request-based processing with integrated workflow, staging, approval, activation, and distribution; the current backfill intent specifically requires engineers who can perform MDG functional, development, and testing activities end to end.

• Analyze business requirements, user stories, process flows, data attributes, and interface mappings, translating them into clear SAP MDG functional and technical solutions.
• Configure and enhance SAP MDG capabilities, including data models, change requests, workflows, user interfaces, validations, derivations, business rules, and replication settings
• Design, develop, and unit-test low- to medium-complexity SAP MDG custom solutions using ABAP, including enhancements, BAdIs, service or proxy extensions, reports, and background-processing logic where required.
• Prepare functional and technical specifications, solution documentation, effort estimates, dependencies, acceptance criteria, and implementation instructions for assigned work packages.
• Plan and execute unit, functional, system, integration, regression, and defect-validation testing; maintain test evidence and support business or user-acceptance testing.
• Troubleshoot MDG configuration, ABAP, workflow, data-quality, replication, and integration issues across development, testing, deployment, and production-support activities.
• Support master-data governance and quality controls through field validation, derivation rules, duplicate prevention, reference-data alignment, mapping checks, reconciliation, and corrective-action analysis.
• Collaborate with integration engineers on inbound and outbound SAP interfaces, including message mapping, error handling, acknowledgments, monitoring, and controlled replication using relevant SAP integration patterns.
• Maintain accurate solution designs, configuration records, code documentation, test scripts, deployment information, runbooks, and support knowledge.
• Work with product owners, business stakeholders, architects, developers, testers, data teams, and integration teams to deliver prioritized backlog items on time and in accordance with architecture, governance, quality, and engineering standards.

Required Qualifications, Experience, and Skills

• Hands-on experience delivering SAP MDG solutions with a combination offunctional analysis, MDG configuration, technical development, testing, and support.
• Mandatory Finance Master Data knowledge, including practical understanding of representative objects such as Chart of Accounts and G/L Accounts, Cost Centers, Profit Centers, Trading Partners, financial reporting structures, hierarchies, and related reference or master data.
• Experience withVendor, Material, and/or Customer Master Data, including the relevant SAP MDG business processes, data models, workflows, validations, extensions, and replication patterns.
• Knowledge of SAP integration technologies and patterns such asSAP PO/PI, SAP Integration Suite/CPI, APIs, IDocs, SOAP or proxy services, enterprise services, and the SAP Data Replication Framework, or equivalent SAP integration approaches
• Strong ABAP development skills are required, including the ability to analyze, develop, debug, test, and support low- to medium-complexity custom MDG solutions. Internal resource planning identifies both MDG functional and MDG ABAP engineering capabilities, while current delivery discussions explicitly reference ABAP MDG work for custom fields and enhancements.
• Experience producing functional and technical specifications and translating business requirements into maintainable configuration and code.
• Strong testing and troubleshooting capability across MDG configuration, ABAP developments, workflows, master data, interfaces, and downstream processing.
• Sound analytical, problem-solving, communication, and documentation skills, with the ability to deliver assigned activities within defined guidelines and collaborate effectively across functional and technical teams.
• Practical experience usingapproved AI-assisted tools to improve requirements analysis, development, code review, test-case creation, documentation, troubleshooting, knowledge retrieval, and day-to-day productivity.

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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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: Proficient

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: Foundational

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: Proficient

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.