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Smartbroker
Smartbroker

(Sr.) Data Engineer (m/f/d)

Data Engineer Berlin · 14 August 2026
Full-time

Your mission

Our significantly growing Data, AI & MarTech Department is looking for an experienced Data Platform Engineer. The position is responsible for improving and continuously further developing our cloud-based data platform – the heart of Smartbroker‘s technical data infrastructure for business analytics & insights. Join us and play a major role in promoting and enabling a truly data-driven culture across the organisation! 

Job description:
  • Develop and improve ourcloud baseddata 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 withhighly ambitiousdata engineers and analysts in our growing Data, AI &MarTechDepartment as well as product technology colleagues
  • Stay up to date with latest market developments in data cloud architecture and share your knowledge

Your profile


    • 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 robust, scalable, and maintainable data pipelines and analytical data models
    • Significant hands-on experience designing and operating data pipelines on cloud-based data platforms (AWS, GCP) using data-native services (S3, Athena, BigQuery…)
    • Strong experience in data warehousing and analytics engineering, ideally including dbt and dimensional data modelling
    • Excellent SQL skills and a deep understanding of data transformation, performance optimisation, and complex analytical queries
    • Deep understanding of software engineering best practices: requirements specification, version control, CI/CD, testing, deployment, and monitoring of data pipelines and transformations
    • Strong programming skills in Python, ideally including orchestration frameworks such as Airflow
    • Experience with data quality, observability, and testing approaches to deliver reliable and trusted data products
    • Knowledge of data streaming technologies like Kafka, Kinesis, Flink and cloud infrastructure is a plus
    • Excellent English communication skills, German is a plus
    • Interest in finance and fintech industry and a sense of humor

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