Senior Data Engineer [M/F]

The project involves building and optimizing data pipelines that support analytics, recommendation systems, and Machine Learning solutions. You will collaborate with Data Science and Engineering teams, ensuring reliability, performance, and high data quality in a production environment.

Daily tasks

• development, maintenance, and optimization of scalable data platforms,
• building and operating complex ETL/ELT pipelines,
• ensuring the reliability of pipelines processing billions of events per day,
• monitoring, observability, and ensuring high data quality,
• solving production issues and ensuring infrastructure stability,
• collaborating with Data Scientists, Analysts, and Engineering teams,
• developing tools and frameworks that support the Data Platform,
• working on solutions related to ML, streaming, and recommendation systems,
• maintaining and developing infrastructure running in a Kubernetes/GKE environment,
• developing Software Engineering and Data Engineering standards.

Requirements

min. 6 years of experience in a Data Engineer role, very good knowledge of Python, SQL, and Spark, experience in building and maintaining large ETL/ELT pipelines, experience with orchestration tools, e.g., Apache Airflow, practical experience with cloud: GCP, AWS, or Azure, experience working with large data volumes, knowledge of Kubernetes, good knowledge of Software Engineering practices, experience with Git and CI/CD, independence and the ability to take responsibility for production systems, very good analytical and problem-solving skills, advanced knowledge of English (min. B2).

Must have: Python, Spark, SQL, ETL, Kubernetes, CI/CD, Git, GCP, AWS, Azure, Data Orchestration

Nice to have: Apache Airflow