Purpose & Overall Relevance for the Organization:

Data engineers builds and optimizes the systems that allow perform proper analytics. They are responsible for data availability and processes around it, the accuracy of the data as well as making it accessible to individuals who need to work with it. The data engineer ensures that any data is properly received, transformed, stored, and made accessible to other users. This role will focus on data availability with a high focus on Japan and Korea, but also provide partial support towards Australia and New Zealand countries.

Key Responsibilities:

• Keep systems running (KSR)
• Ensure uninterrupted access to critical data resources for all authorized users.
• Implement high availability and disaster recovery solutions to minimize downtime.
• Monitor system performance and take proactive measures to prevent data unavailability
• Establish and maintain data quality standards and guidelines.
• Collaborate with data stakeholders to identify and address data quality issues.
• Implement data cleansing and enrichment processes as necessary.
• Oversee data pipelines and ETL (Extract, Transform, Load) processes.
• Implement monitoring and alerting systems to detect pipeline failures or data inconsistencies.
• Troubleshoot and resolve pipeline issues promptly to maintain data integrity.
• Collaborate with database administrators, data engineers, and other Data or IT teams to achieve KSR objectives
• Specialist advice
• Actively maintains knowledge in one or more identifiable specialisms.
• Provides detailed and specific advice regarding the application of their specialism(s) to the organization's planning and operations.
• Recognizes and identifies the boundaries of their own specialist knowledge.
• Collaborates with other specialists, where appropriate, to ensure advice given is appropriate to the needs of the organization.
• Emerging technology monitoring
• Supports monitoring of the external environment and assessment of emerging technologies to evaluate the potential impacts, threats, and opportunities to the organization.
• Contributes to the creation of reports, technology road mapping and the sharing of knowledge and insights.
• Data modelling & design
• Investigates corporate data requirements, and applies data analysis, design, modelling, and quality assurance techniques, to establish, modify or maintain data structures and their associated components (entity descriptions, relationship descriptions, attribute definitions).
• Provides advice and guidance to database designers and others using the data structures and associated components.
• Database design
• Develops and maintains specialist knowledge of database and data warehouse concepts, design principles, architectures, software and facilities.
• Assesses proposed changes to object/data structures, in order to evaluate alternative options.
• Implements physical database designs to support transactional data requirements for performance and availability.
• Implements data warehouse designs that support demands for business intelligence and data analytics.
• Programming/software development
• Designs, codes, verifies, tests, documents, amends, and refactors complex programs/scripts and integration software services.
• Contributes to selection of the software development approach for projects, selecting appropriately from predictive (plan-driven) approaches or adaptive (iterative/agile) approaches.
• Applies agreed standards and tools, to achieve well-engineered outcomes.
• Participates in reviews of own work and leads reviews of colleagues' work.
• Testing
• Reviews requirements and specifications and defines test conditions.
• Designs test cases and test scripts under own direction, mapping back to pre-determined criteria, recording, and reporting outcomes.
• Analyses and reports test activities and results.
• Identifies and reports issues and risks associated with own work.
• Data management
• Assists in providing accessibility, retrievability, security and protection of data in an ethical manner.
• SCRUM framework
• Good understanding and experience of SCRUM framework
• Software Knowledge
• Database: Exasol, SQL Server, Databricks, AWS, or knowledge in similar technologies.
• Language: Python, SQL, Apache Spark .
• Source code management tool: GIT, Bitbucket, notebooks.
• Project Management Tool: JIRA, Confluence, MS Project
• Reporting tool: MicroStrategy, Power BI would be a plus

If required: People Management / Resource Management:

• May be involved and gives some input on hiring Transition decisions
• Ensures appropriate leadership skills are present at every level through creating a motivational and supportive work environment in which employees are coached, trained, and provided with career opportunities through development
• Allocates the different work to the respective employees considering experience, complexity, workload, and organizational efficiency
• Continuously monitors and evaluates team workload and organizational efficiency with the support of IT systems, data and analysis and team feedback and makes appropriate changes to meet business needs.
• Provides team members/direct reports with clear direction and targets that are aligned with business needs and GIT objectives

Key Relationships:

• Global DNA team
• Global DevOps team
• Global Data Engineering
• DNA Market teams
• Global and Local IT
• Respective business function (GOPS, Finance, eCom, HR, Brand Marketing, Wholesale/Retail)
• Country Cluster cross functional team

Requisite Education and Experience / Minimum Qualifications:

• University degree in the field of Business, Information Technology or equivalent
• >5 years of experience in data management and analytics
• Proficient spoken and written command of English is a must
• Experience in working in a diverse and global team preferable
• Experience with BI tool management (Microstrategy, PowerBI, Tableau or other tool)
• Experience with analytics tools and disciplines (SQL, Python, Apache Spark , database management ..).
• Project management skills, including the ability to lead projects or work on several projects simultaneously
• Proficient in MS Office
• Experience in data engineering with Databricks and AWS S3 preferred