Das ist der Job
Responsibilities Design, build, and operate data pipelines and platforms.
Darum lohnt es sich
Collaborate closely with cross-functional teams and clients. Team player: enjoy working with data scientists, analysts, and clients. Proficient in cloud environments and automation tools, ensuring efficient data workflows and collaboration with cross-functional teams. #J-18808-Ljbffr Develop, test, and operate robust ETL/ELT pipelines.
Design and maintain data models, schemas, and structures for data warehouses/lakehouses. Implement validations, quality checks, and monitoring. Build and optimize data solutions in the cloud (AWS/Azure/GCP). Automate recurring data workflows (e.g., using Airflow) and ensure clean deployments with CI/CD.
Requirements Data engineering experience: built and operated production data pipelines and infrastructure. Tool stack: proficient in Python and SQL, familiar with ETL/ELT, data warehouses/lakehouses, and cloud environments (Databricks/Snowflake/AWS/Azure/GCP).
Data modeling & quality awareness: understand data modeling and prioritize data quality, testing, and maintainable code. Execution skills & ownership: pragmatically and purposefully drive solutions from concept to production and take responsibility for results and quality. Languages: fluent German (C1+); strong English skills are a plus.
Core Competencies Demonstrates expertise in designing and operating data pipelines and platforms, with a strong focus on ETL/ELT processes, data modeling, and quality assurance.
