Currently we are looking for Data Engineer who will join project from logistics industry. You will play a key role in shaping the company-wide data ecosystem, enabling data-driven decision-making across the operations. Your primary focus will be on implementing robust pipelines and building a scalable, high-performance data infrastructure to support various stakeholders in fleet management, operations, and sustainability.

Work Mode: 100% remote

Duration of the project: 6 months (with possibility of extension)

• Develop and maintain efficient ETL/ELT processes to collect and transform large-scale data from vessel-based systems
• Optimize and manage data workflows in cloud environments such as AWS and Databricks, ensuring high performance, reliability, and data integrity
• Design and implement structured data models and architectures that align with business objectives
• Establish CI/CD pipelines for automated testing, deployment, and seamless integration of data solutions
• Apply DevOps best practices and tools like Jenkins, GitLab CI/CD, Docker, and Kubernetes to enhance the development and deployment of data services
• Assist Data Scientists and BI teams by providing well-structured datasets and improving query performance for advanced analytics

• Min. 4 years of experience on a similar position
• Extensive experience with AWS cloud services, data lakes, and big data technologies, with preference for expertise in Databricks, Redshift, or Snowflake
• Strong command of Python, PySpark, and SQL, particularly in the context of building scalable and efficient data pipelines
• Hands-on knowledge of DevOps tools like Docker and Kubernetes, as well as CI/CD pipelines such as Jenkins or GitLab CI/CD to support continuous integration and deployment
• Familiarity with orchestration tools like Apache Airflow for managing and automating complex data workflows
• A solid grasp of data governance best practices, security protocols, and regulatory compliance requirements
• Demonstrated capability to diagnose and resolve complex issues, optimize performance, and apply industry best practices in data engineering
• Proficiency in business English (min. B2), both written and spoken.
• Nice to have: prior experience in application management or operational procedures within the logistics or shipping industry