Develop and improve our cloud based data platform for data analytic and business insights using most innovative data technologies
Build end-to-end data pipelines from raw data ingestion to consumable data: prepare and clean structured and unstructured data and develop high-quality data models for advanced analytics and AI use cases
Implement data quality monitoring to ensure accuracy and reliability of data pipelines
Architect, code, and deploy data infrastructure components
Collaborate closely with highly ambitious data engineers and analysts in our growing Data, AI & MarTech Department as well as product technology colleagues
Stay up to date with latest market developments in data cloud architecture and share your knowledge

University degree in computer science, mathematics, natural sciences, or a similar field
Several years of experience in data engineering and strong know-how in building data-native, robust, scalable, and maintainable data platforms
Significant hands-on experience designing and operating data pipelines on cloud based data platforms (AWS, GCP) using data-native services (S3, Athena, BigQuery …)
Experience in data warehousing and containerization, e.g., Kubernetes, Docker…
Advanced knowledge about cloud networking & security (IAM, security groups…)
Proficient and experienced with Infrastructure as Code
Deep understanding of software engineering best practices: requirements specification, version control, CI/CD, testing, deployment, and monitoring of data pipelines and services
Excellent SQL skills and strong programming skills in Python, ideally including Airflow and PySpark
Strong knowledge in data streaming technologies like Kafka, Kinesis, Flink…
Excellent English communication skills, German is a plus
Interest in finance and fintech industry and a sense of humor.

Senior Data Platform Engineer

Key skills