Data Engineer (Middle/Senior)

The project focuses on building a cloud-based logistics analytics platform that provides standardized, high-quality reporting and insights across complex, global supply chain processes. The solution is designed to support data-driven decision-making by making logistics data transparent, reliable, and easy to consume for business users across multiple organizational units.

Built on modern cloud technologies, the platform combines scalable data warehousing, automated data pipelines, and strong data governance to transform large volumes of logistics data into trusted KPIs and analytical datasets. It plays a critical role in improving efficiency, visibility, and operational performance across the end-to-end logistics value stream.

We’re looking for someone who truly understands data flows, thinks analytically, and can see the bigger picture beyond individual tasks. If you’re curious, ask the right questions, and enjoy bringing smart ideas to the table, we’re open to some flexibility in specific requirements. Finding the right person matters more to us than ticking every box. 

• Implement business logic in the Data Warehouse in accordance with functional and technical specifications
• Perform light business analysis to ensure data is delivered accurately and in a meaningful, business-relevant way
• Translate business requirements into scalable and efficient data models
• Design, build, and maintain ETL pipelines using Azure Data Factory
  
• Optimize data loading processes and tune query performance
• Collaborate closely with senior stakeholders on the customer side to refine requirements and propose data-driven improvements
• Actively contribute ideas and solutions to improve data architecture and pipeline reliability

• 3+ years of experience working with Microsoft Azure and readiness to work primarily with SQL (up to 80% of the time)
• Proven experience in database development using MS SQL Server / T-SQL
  
• Ability to write highly performant SQL and implement performance optimization techniques
• Hands-on experience with version control systems (e.g. Git)
• Solid understanding of data warehousing concepts and dimensional modeling
  
• Experience working in an Agile development environment
• Practical knowledge of creating and maintaining Azure DevOps and Azure Data Factory pipelines
• Experience developing robust data pipelines using dbt
  

• Experience with Databricks
  
• Background in Supply Chain & Logistics projects
• Familiarity with SAP MM data structures