onsite
Data & Integration Engineer - GFE Metalle und Materialen GmbH
Implementation Engineer
Lead end‑to‑end data integration projects, building scalable pipelines with Python, SQL, and Spark on AWS. Design and maintain data models, ensure data quality, and collaborate with cross‑functional teams to deliver actionable insights.
About the role
Key Responsibilities
- Design, develop, and maintain robust ETL pipelines using Python, SQL, and Spark on AWS infrastructure.
- Collaborate with data scientists and business stakeholders to define data requirements and translate them into scalable integration solutions.
- Implement data quality checks, monitoring, and alerting to ensure high data integrity across all pipelines.
- Optimize existing data workflows for performance, cost, and maintainability.
- Document data models, pipeline architecture, and best practices for future reference.
Requirements
- Proven experience in data engineering with Python, SQL, and Spark.
- Hands‑on knowledge of AWS services such as S3, Redshift, Glue, and Lambda.
- Strong understanding of data modeling, schema design, and ETL best practices.
- Experience with version control (Git) and CI/CD pipelines for data workflows.
- Excellent problem‑solving skills and ability to work independently in a fast‑paced environment.