WOFÜR WIR SIE SUCHEN

Design and implement a structured lakehouse architecture that balances high-performance data access with cost-efficient storage management
Build and operate reliable data ingestion pipelines for large-scale earth observation and sensor data in both batch and streaming scenarios
Ensure robust metadata extraction, schema validation, and data quality checks throughout the ingestion process
Optimize data processing performance by implementing efficient partitioning, tiling strategies, and minimizing unnecessary data movement.
Enable high-performance analytics by designing data layouts that allow compute workloads to operate close to the storage layer
Implement comprehensive data lineage and versioning to ensure full traceability and historical reproducibility of datasets
Establish and maintain strong data governance standards including access controls and secure data handling practices
Continuously improve the scalability, reliability, and operational performance of the data platform
Successfully completed studies in computer science, data engineering, information systems, or a comparable qualification
Several years of professional experience in data engineering and building large-scale distributed data platforms
Strong experience designing and operating modern data lake or lakehouse architectures for high-volume datasets
Expertise in distributed data processing frameworks and performance optimization for large-scale workloads
Experience building reliable data ingestion pipelines and managing complex data transformation workflows
Practical experience implementing data versioning, lineage tracking, and reproducible data workflows
Structured and analytical approach to solving complex data engineering challenges
Strong collaboration and communication skills when working with cross-functional engineering and analytics teams

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Data Engineer (m/f/d)