MDG Data Architect
Kardex is on a transformational journey to develop global
-
- end (E2E) business processes across all regions and functions and improve our customer and employee experience. We have launched a global program called North
Star and using SAP S/4HANA will build bridges to operational and organizational excellence, transforming Kardex into a high performance, digital organization with harmonized and integrated
-
- end processes.
We are now seeking an experienced Data Architect who can support the Senior Data Lead on the global projects to effectively design, manage and deliver master data requirements for all
-
- end processes and systems and that master data quality is maintained thereafter.
In your role, you will ensure that master data is accurate, accessible, available, and consistent for use across the organisation.
As a Data Architect, you will be responsible for designing, developing, and maintaining the organization's data architecture to ensure data integrity, security, availability, and accessibility within SAP MDG. You will collaborate closely with stakeholders from various departments to understand their data needs and develop strategies to meet those needs effectively. Your role will involve designing data models, establishing data management policies and procedures, and overseeing data governance initiatives. You will also be responsible for evaluating and implementing data technologies and tools to optimize data storage, processing, and retrieval capabilities.
A Data Architect plays a critical role in shaping the Kardex data landscape and ensuring that data assets are managed effectively to drive business value. Your expertise in data architecture, governance, and technology will be essential in enabling
- driven
- making and fostering innovation across the organization.
You will act as a brand ambassador by modelling the Kardex Remstar Core Values in every interaction with customers & colleagues and be the face of the Global MDG Team at our customer sites across the country.
In this important role you must prove to be flexible and willing to commit the time and effort necessary to meet the organization’s needs to ensure customer satisfaction and loyalty during every interaction.
Your tasks
Responsibilities
Data Architecture Design: Develop and maintain the organization's data architecture by designing conceptual, logical, and physical data models that align with business objectives and support data integration, storage, and analysis requirements.
Data Management Policies and Procedures: Define and implement data management policies, standards, and best practices to ensure consistent data quality, integrity, security, and compliance with regulatory requirements.
Data Governance: Establish data governance frameworks and processes to govern data assets, including data stewardship, data quality management, metadata management, and data access controls.
Data Integration and ETL: Design and implement data integration strategies and ETL (Extract, Transform, Load) processes to ensure seamless data flows between disparate systems and applications.
Data Technology Evaluation and Implementation: Evaluate emerging data technologies, tools, and platforms to enhance data processing capabilities, scalability, and performance. Lead the implementation of selected technologies and oversee their integration into the existing data ecosystem.
Collaboration and Stakeholder Management: Collaborate with stakeholders from various business units to understand their data requirements and translate them into actionable data solutions. Serve as a trusted advisor to business leaders on
- related matters.
Data Analysis and Reporting: Perform data analysis to identify trends, patterns, and insights that can inform business
- making. Develop and maintain data dashboards, reports, and visualizations to communicate key findings to stakeholders.
Training and Knowledge Sharing: Provide training and guidance to internal teams on data management best practices, tools, and technologies. Promote a culture of
- driven
- making and continuous learning within the organization.
Your profile
Training/Education:
Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
Proven experience (5 years) in data architecture, data modeling, and database design.
In-depth knowledge of data management concepts, practices, and technologies (e. g. , relational databases, data warehousing, big data platforms, cloud services).
- Experience with data governance frameworks, data quality management, and metadata management.
- Proficiency in SAP MDG.
- Strong analytical and
- solving skills, with the ability to translate business requirements into technical solutions. - Excellent communication and interpersonal skills, with the ability to collaborate effectively with
- functional teams and stakeholders. - Any other relevant certifications are a plus.
Professional Experience
- Proficiency in data management principles, data governance practices, and data quality concepts.
- Familiarity with data modelling, data integration, and data lineage.
- Strong understanding of the organization's industry, business processes, and data requirements. This domain knowledge is crucial for effective data architectural design.
- Ability to work with data governance & management tools, data quality software, metadata management systems, preferably SAP-MDG.
- Strong analytical and
- solving skills to identify data quality issues and recommend solutions.
Leadership/Other
- Understanding of relevant data privacy regulations (e. g. , GDPR, CCPA) and
- specific compliance requirements. - Capability to manage tasks and projects related to data governance initiatives.
- Willingness to work in
- functional teams and facilitate discussions around data requirements and governance. - Relevant experience in data management, data analysis, data quality assurance, or related roles.
- Ability to work in a geographically spread Data Management Team.
- Confident, strong assertive team player.
- Customer oriented.
- Socially presentable.
- Good interpersonal skills.
- Methodological skills.
- Experience in a data driven industrial production environment is a plus.
- Local language proficiency.
- English CEFR Level B2.
- Willingness to travel occasionally.
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