Data Engineer

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Skills you'll use

What you'll do

• Data Engineering & Architecture
• Design and maintain robust, scalable data pipelines using Kubeflow, Python, and Snowflake, ensuring optimal performance and reliability.
• Follow best practice standards for deployment and the use of CI/CD tools.
• Govern end-to-end data architecture with a focus on data quality, security, compliance, and lifecycle management.
• Expertise in Requirements engineering and refinement
• Build efficient and scalable data models ensuring optimal query performance and responsiveness.
• Ensure seamless data flow across ingestion layers, data models, and visualization outputs.
• Analytics & Visualization
• Conduct in depth data analysis to identify trends, variances, and improvement opportunities, transforming insights into clear and actionable recommendations for business stakeholders.
• Translate complex datasets into actionable insights through Power BI dashboards.

Who can apply

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• Minimum 3 years of experience in data engineering, analytics, or business intelligence
• Technical Skills
• Experience in Kubeflow / Similar Orchestrator tool (mandatory), Python (mandatory), and Snowflake (or similar DBMS)
• Experience working with GitHub including its CI/CD capabilities
• Experience in developing, evaluating and serving ML and AI solutions preferably
• Experience in Power BI or similar applications (e.g. Tableau) preferable
• Strong understanding of data structures and reporting standards
• Proficiency with Microsoft Office 365 tools (Excel, Word, PowerPoint, Outlook), including advanced Excel functions for analysis and reporting.
• Excellent communication and stakeholder management skills in English; German language skills are an advantage.

Perks & benefits

About DHL Group

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