We are noticing many open positions in Europe with SPA Technical / Techno-Functional skills. Are you open to an international career and considering relocating to Europe? Share your CV and connect with us. About the Role We are seeking a skilled and driven Data Engineer to join a high-growth international team based in Europe. In this role, you will design, build, and maintain robust data pipelines and infrastructure that power business intelligence and advanced analytics. You will work closely with data scientists, analysts, and product teams to ensure that data is accessible, reliable, and ready for use. Key Responsibilities Design, develop, and maintain scalable ETL/ELT data pipelines using modern orchestration tools (e.g., Apache Airflow, dbt, Prefect). Build and manage data warehouses and data lakes on cloud platforms (AWS, GCP, or Azure). Ensure data quality, integrity, and availability across all data systems and platforms. Collaborate with data scientists and analysts to model, transform, and deliver clean datasets for reporting and ML workloads. Optimize query performance and database architecture for speed and scalability. Implement data governance standards, access controls, and documentation best practices. Monitor and maintain data infrastructure, proactively identifying and resolving bottlenecks or failures. Contribute to migration and modernization of legacy data systems to cloud-native architectures. Work in an Agile environment, participating in sprint planning, standups, and retrospectives. 4 years of hands-on experience in data engineering, data architecture, or a related role. Proficiency in Python and/or Scala for data processing and pipeline development. Strong SQL skills with experience in query optimization and data modeling. Experience with big data technologies such as Apache Spark, Kafka, or Flink. Hands-on experience with cloud data platforms: AWS (Redshift, Glue, S3), GCP (BigQuery, Dataflow), or Azure (Synapse, Data Factory). Familiarity with data modeling techniques (Star Schema, Data Vault, etc.). Experience with version control (Git) and CI/CD pipelines for data workflows. Strong understanding of data warehousing concepts, dimensional modeling, and lakehouse architecture. Excellent communication skills with the ability to explain complex data concepts to non-technical stakeholders. Experience with SAP data extraction and integration (SAP BW, SAP HANA, or SAP Data Services). Exposure to real-time streaming architectures. Knowledge of dbt (data build tool) for transformation workflows. Experience working in multinational or distributed Agile teams. Familiarity with GDPR and European data privacy regulations. Required Skills & Qualifications Nice to Have