Data Engineer

We are looking for a Data Engineer for a fully remote position.

About the Role

You will build the data foundation for AI initiatives, making operational, customer, parcel and business data available in reliable, well-structured, governed and scalable pipelines so that AI teams and agentic workflows can turn data into measurable business impact. You work closely with data scientists, AI engineers, cloud engineers, business process owners and country IT teams to design, implement, operate and improve data pipelines, data products and analytical datasets across enterprise systems.

You are a hands-on data engineer who enjoys turning messy enterprise data into reliable data products. You understand that AI success depends on clean, available, well-governed data and you are comfortable working with both technical teams and business stakeholders.

Main Responsibilities

• Design, build and operate enterprise-grade ETL and ELT pipelines for AI, analytics, reporting and agentic workflow use cases.
  
• Create clean, documented and reusable data products from operational, customer, logistics, sales and other data sources.
  
• Implement data quality checks, monitoring, lineage, metadata and reliability patterns to make datasets trustworthy and production-ready.
  
• Support integrations between Azure-based AI services, Snowflake, APIs, file-based sources and selected AWS data services where needed.
  
• Work with business and AI teams to translate use case requirements into data models, pipelines and serving layers.
  
• Collaborate with local IT and data owners to onboard new data sources while respecting data protection, access control and governance requirements.
  

Requirements

• Strong experience with Python, SQL, data modelling, ETL/ELT development and production data pipelines.
  
• Experience with cloud-native data engineering, ideally on Azure, with practical AWS exposure as a plus.
  
• Experience with Snowflake or comparable cloud data platforms.
  
• Understanding of data quality, orchestration, observability, access management and governance in enterprise environments.
  
• Ability to collaborate with data scientists, AI engineers, business stakeholders and local IT teams in international settings.
  
• Comfortable using GenAI software engineering tools such as GitHub Copilot, Cursor or OpenCode to accelerate development.
  
• Fluent English.
  

Nice to Have

• Experience with Iceberg, AWS Glue, Spark, Databricks or similar data engineering technologies.
  
• Experience with logistics, parcel operations, customer feedback, route, depot or sales data.
  
• Exposure to AI feature stores, vector databases, retrieval pipelines or data preparation for GenAI applications.