Das ist der Job
Implement and orchestrate ETL workflows using Apache Airflow, ensuring data quality and timely delivery.
Darum lohnt es sich
Key Responsibilities Design, develop, and maintain robust Python‑based data pipelines for large‑scale rating model inputs. Build and optimize distributed data processing jobs with Apache Spark for simulation and analytics. Collaborate with quantitative analysts to translate model requirements into scalable data solutions.
Deploy and monitor data services on AWS, leveraging services such as S3, Redshift, and Lambda. Maintain version control, documentation, and automated testing for all code artifacts. Requirements 5+ years of professional experience in Python development and data engineering. Strong proficiency in SQL and relational database design.
Hands‑on experience with Apache Airflow and Apache Spark in production environments. Solid understanding of AWS cloud services and infrastructure as code. Ability to work independently, solve complex analytical problems, and communicate technical concepts to non‑technical stakeholders.
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