Riverty Group GmbH
10623 Berlin - Deutschland
Informatiker/in
Arbeit
Vollzeit
ab 01.04.2026
Beschreibung
We are looking for a
(Senior) Data Engineer (m/f/d)
(unlimited, full-time) Join our team at our location in Berlin - hybrid working conditions available
As part of our Data Engineering team, you’ll design, build, and maintain robust data pipelines using Azure Data Factory, Databricks, Airflow, and other cloud-native tools. You'll shape how we ingest, transform, and serve data across our organization-powering analytics, reporting, and decision-making at scale.
This is a hands-on, impact-d... weiter lesen
(Senior) Data Engineer (m/f/d)
(unlimited, full-time) Join our team at our location in Berlin - hybrid working conditions available
As part of our Data Engineering team, you’ll design, build, and maintain robust data pipelines using Azure Data Factory, Databricks, Airflow, and other cloud-native tools. You'll shape how we ingest, transform, and serve data across our organization-powering analytics, reporting, and decision-making at scale.
This is a hands-on, impact-d... weiter lesen
We are looking for a
(Senior) Data Engineer (m/f/d)
(unlimited, full-time) Join our team at our location in Berlin - hybrid working conditions available
As part of our Data Engineering team, you’ll design, build, and maintain robust data pipelines using Azure Data Factory, Databricks, Airflow, and other cloud-native tools. You'll shape how we ingest, transform, and serve data across our organization-powering analytics, reporting, and decision-making at scale.
This is a hands-on, impact-driven role for someone who enjoys working across big data, cloud platforms, and data infrastructure. You’ll collaborate with product, analytics, and engineering teams across countries and functions.
What you are expected to do:
Design and implement scalable ETL/ELT pipelines in a lakehouse architecture using Databricks, Azure Data Factory, Azure Data Lake, and other modern tools.
Create analytical data models and structures optimized for performance and usability.
Drive best practices in data engineering, including CI/CD with Azure DevOps, Git workflows, testing, and monitoring.
Integrate workflows and orchestration using Airflow and other tools as needed.
Troubleshoot, monitor, and improve data quality, pipeline reliability, and job performance across distributed systems.
Work with stakeholders to understand data requirements and deliver scalable, maintainable solutions.
Stay on top of trends in cloud data platforms, open-source frameworks, and engineering practices.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
5+ years of experience in data engineering, with a focus on cloud-native platforms.
Hands-on expertise with Azure Data Factory, Databricks, Azure Data Lake, SQL, and Python.
Familiarity with DevOps workflows (e.g., Git, Azure DevOps) and orchestration tools like Airflow.
Solid understanding of data warehousing, data modeling, and modern data architecture.
Strong communication skills and the ability to work cross-functionally with business and technical stakeholders.
A proactive mindset, capable of owning outcomes and navigating ambiguity.
(Senior) Data Engineer (m/f/d)
(unlimited, full-time) Join our team at our location in Berlin - hybrid working conditions available
As part of our Data Engineering team, you’ll design, build, and maintain robust data pipelines using Azure Data Factory, Databricks, Airflow, and other cloud-native tools. You'll shape how we ingest, transform, and serve data across our organization-powering analytics, reporting, and decision-making at scale.
This is a hands-on, impact-driven role for someone who enjoys working across big data, cloud platforms, and data infrastructure. You’ll collaborate with product, analytics, and engineering teams across countries and functions.
What you are expected to do:
Design and implement scalable ETL/ELT pipelines in a lakehouse architecture using Databricks, Azure Data Factory, Azure Data Lake, and other modern tools.
Create analytical data models and structures optimized for performance and usability.
Drive best practices in data engineering, including CI/CD with Azure DevOps, Git workflows, testing, and monitoring.
Integrate workflows and orchestration using Airflow and other tools as needed.
Troubleshoot, monitor, and improve data quality, pipeline reliability, and job performance across distributed systems.
Work with stakeholders to understand data requirements and deliver scalable, maintainable solutions.
Stay on top of trends in cloud data platforms, open-source frameworks, and engineering practices.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
5+ years of experience in data engineering, with a focus on cloud-native platforms.
Hands-on expertise with Azure Data Factory, Databricks, Azure Data Lake, SQL, and Python.
Familiarity with DevOps workflows (e.g., Git, Azure DevOps) and orchestration tools like Airflow.
Solid understanding of data warehousing, data modeling, and modern data architecture.
Strong communication skills and the ability to work cross-functionally with business and technical stakeholders.
A proactive mindset, capable of owning outcomes and navigating ambiguity.
Ref-Nr.: 10148740
Aktualisiert:
01.04.2026
Quelle: Bundesagentur für Arbeit
weitere Infos Rechtliche Hinweise zur Nutzung
Ob die Stelle noch verfügbar ist und weitere Informationen findest du direkt auf der Website der Bundesagentur für Arbeit. Bitte beachte: OPROMA ist nicht der Anbieter dieser Stelle und kann keine Auskünfte geben.
weitere Infos Rechtliche Hinweise zur Nutzung
Ob die Stelle noch verfügbar ist und weitere Informationen findest du direkt auf der Website der Bundesagentur für Arbeit. Bitte beachte: OPROMA ist nicht der Anbieter dieser Stelle und kann keine Auskünfte geben.
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