SAP Data Migration Consultant
About the Role
Maersk is seeking experienced Data Migration Consultants to join our growing Data team. The ideal candidate will have a strong background in SAP data migration projects and hands-on expertise in SAP Data Services (BODS), SQL/HANA development, and ETL processes.
This role will be responsible for delivering end-to-end data migration activities across large-scale SAP implementations, ensuring data quality, successful data loads, and reconciliation throughout the migration lifecycle.
Key Responsibilities
- Design, develop, and support data migration solutions using SAP Data Services (BODS).
- Execute data migration activities for Greenfield and Brownfield SAP implementations.
- Develop and optimize SQL and SAP HANA scripts, procedures, and data validation routines.
- Build and maintain ETL processes for data extraction, transformation, cleansing, and loading.
- Support data loading activities using LTMC (Legacy Transfer Migration Cockpit) and other SAP migration tools.
- Perform data quality checks and execute pre-load and post-load reconciliation activities.
- Analyze and resolve data issues in collaboration with business users, functional consultants, and technical teams.
- Support mock loads, dress rehearsals, cutovers, and production go-live activities.
- Contribute to migration automation, reusable frameworks, and continuous process improvement initiatives.
Required Skills
- 5-8 years of working experience in SAP Data Migration projects as techno-functional consultant.
- Strong hands-on experience with SAP Data Services (BODS).
- Proven experience supporting Greenfield and Brownfield SAP implementations.
- Strong understanding of Master & Transactional Objects in ATR, OTC and PTP value stream
- Strong SQL development skills and experience with SAP HANA.
- Solid understanding of ETL concepts and data transformation frameworks.
- Experience with LTMC data loads and SAP migration methodologies.
- Hands-on experience in pre-load and post-load reconciliation processes.
- Strong analytical and problem-solving capabilities.
Nice to have
- Experience in Power BI development, reporting, and dashboard creation.
- Generative AI exposure to automate the manual tasks to increase productivity
- S4 MDG experience will be a plus.
- Familiarity with Master data deduplication will be added advantage.
- Experience working in global transformation or ERP migration projects.
- Familiarity with data quality, validation, and governance practices.
- Hands on python experience will be a plus.
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 [email protected].
CORE SKILLSData 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.