Minimum 7 years of experience in Data Engineering, Strong background in designing and implementing scalable data processing systems (pipelines, ETL processes, data warehouses, and data lakes), Hands-on experience with implementing data warehousing solutions like Snowflake, Databricks or Apache Iceberg, Strong background and at least 3 years of hands on experience in either AWS or Azure data engineering services, Practical experience with dbt for data transformation, Strong SQL skills and experience with relational databases, Familiarity with Apache Airflow for workflow orchestration, Proficiency in Python for data engineering tasks, Strong problem-solving and analytical thinking abilities, Good communication skills in English (minimum B2 level)

sharing the costs of sports activities, private medical care, life insurance, remote work opportunities, flexible working time, integration events, computer available for private use, corporate library, no dress code, video games at work, coffee / tea, drinks, parking space for employees, leisure zone