Senior Data Engineer - Data Analytics Platform 80-100% (f/m/d)

Tasks

• Develop and maintain end-to-end data pipelines using Python or Scala to ensure a smooth data flow and integrate data from various sources
• Ensuring data completeness and scalability; managing data loading processes and data quality
• Diagnosing the causes of errors and identifying solutions, optimizing ETL/ELT pipelines
• Mentoring and guiding junior developers on best practices in data engineering

Requirements

• Bachelor's or Master's degree with a focus on computer science, data analysis, information systems, or a related technical field, or equivalent education and professional experience
• More than 5 years of experience in ETL/ELT, data warehousing, business intelligence, and the integration of data processing and workflow management tools into pipeline design
• More than 5 years of experience in the development and maintenance of end-to-end data systems using Python, Scala, or similar programming languages
• Extensive experience using SQL for data analysis, investigating data issues, and designing effective solutions
• Experience working with cloud-based data technologies, preferably on Microsoft Fabric, including experience with Azure Databricks, Azure SQL Warehouse, Azure Synapse Analytics, and similar streaming technologies, as well as Delta Lake
• Proven experience working with large datasets, utilizing data engineering skills in system design, implementation, and testing
• Familiarity with cloud storage solutions such as Azure Data Lake and Blob Storage
• In-depth knowledge of data modeling principles (experience with Data Vault is a plus) and strong skills in system design, implementation, and testing
• Experience with event-driven architectures (e.g., Kafka, Event Hubs, Apache Flink) is a plus, and experience with containerized deployment (e.g., Docker, Kubernetes) is advantageous