Data Engineer

Join the Future of Financial Intelligence at DHL

DHL Group the logistics provider of the world with over 580,000 employees in more than 220 countries and territories. We are an organization that is not just moving goods around, we have a very clear purpose, and we are: Connecting People. Improving Lives. We provide challenges and opportunities for personal and professional development, we recognize the difference you bring to our business and together we share the pride of building one of the largest world leaders in logistics and supply chain.

Are you ready to shape the next generation of financial steering within one of the most dynamic logistics environments in the world

The Financial Intelligence Solutions department for a German speaking country is at the forefront of transforming how financial data drives business decisions. We deliver real-time, business-critical insights across reporting, forecasting, and planning - empowering leadership with the intelligence needed to act with precision and speed.

But we don't stop there.

We are pioneering the digitalization of financial processes, integrating cutting-edge technologies and emerging trends to redefine how data creates value. Our mission is clear: to turn information into impact and unlock measurable business advantage through smart, scalable, and future-proof solutions.

What sets us apart is our strong team spirit - a culture of collaboration, mutual support, and shared ambition. We believe that the best ideas emerge when diverse minds come together, and we foster an environment where everyone contributes to shaping the future.

If you're a visionary professional with a passion for data-driven strategy, digital innovation, and operational excellence - this is your opportunity to make a difference at scale.

Step into a role where your expertise fuels transformation. Shape the future with us.

Key Responsibilities

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.
• Apply DAX and Power Query techniques to create dynamic, user friendly, and high performance visualizations for operational and analytical use cases.
• Collaborate with business stakeholders, strategy, and IT stakeholders to define KPIs, reporting standards, and analytical models that support strategic decision-making.
• Perform ad-hoc analysis and maintenance tasks.

Collaboration & Documentation

• Maintain version control, documentation, and workflow traceability in GitHub to ensure transparency, reproducibility, and collaboration across teams.
• Work closely with business stakeholders to gather requirements, validate outputs, and iteratively refine solutions.

Education & Experience

• 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