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Data Engineer
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About this role
Role overview Build and maintain data platforms that support operational reporting, supply-chain processes, and forecasting across multiple markets. The work combines hands-on pipeline development with data architecture and gradual platform modernization in a cloud environment, with an emphasis on reliable delivery and long-term stability.
Responsibilities - Build and optimize data pipelines and models in BigQuery. - Create, maintain, and automate Airflow workflows. - Develop scalable data workflows in Python. - Enhance and operate a large Google Cloud data environment. - Partner with analysts and data scientists to turn business needs into robust data solutions. - Own data quality, reliability, and operational continuity while contributing to platform evolution.
Requirements - Strong practical experience with BigQuery, Airflow, and Python. - Good understanding of Google Cloud data services. - Strong SQL and data-modelling fundamentals. - Basic DevOps knowledge, including Kubernetes, service accounts, and CI/CD fundamentals. - Able to work independently and deliver reliably across both development and maintenance. - Comfortable collaborating in a distributed, multicultural environment.
Nice to have Familiarity with machine learning models or MLOps concepts.
Benefits and work setup Work with small teams that own what they deliver, on long-term enterprise programs with stable roadmaps. The role includes structured internal technical enablement.