About the Role
We are seeking a skilled Data Engineer to design and implement modern data integration solutions that empower organizations to unlock the true value of their data.
The ideal candidate will have a passion for building seamless data pipelines and driving innovation in cloud-based data environments.
They will excel at transforming raw data into valuable insights, leveraging tools like Azure Data Factory and Databricks.
Responsibilities:
* Data Pipeline Development: Design, build, and maintain end-to-end data pipelines using Azure Data Factory, ensuring efficient and reliable data ingestion and transformation processes.
* Databricks Expertise: Leverage Databricks to perform advanced data processing, enabling seamless integration with data lakes and warehouses while optimizing Spark-based workflows.
* Scalable and Reliable Solutions: Architect scalable, cloud-native solutions that meet modern data integration and transformation needs while maintaining data quality and governance standards.
* CICD for Cloud Platforms: Bring expertise in CI/CD pipelines with tools such as Azure DevOps or GitLab, ensuring streamlined code deployment and system updates while maintaining robust security and compliance practices.
* Cross-Team Collaboration: Work closely with data analysts, scientists, and stakeholders to ensure the data architecture aligns with business objectives and analytical needs.
Requirements:
* Education: Bachelor's degree in Computer Science, Data Engineering, or a related field.
* Experience: 5+ years of experience in data engineering or related roles.
* Technical Skills: Hands-on experience with Azure Data Factory and Databricks. Familiarity with Fivetran and PowerBI is a plus.
* Language Proficiency: Proficiency in English (German is a bonus).
Desired Qualities:
* Innovative Problem-Solving: Enjoy tackling complex data challenges and devising efficient solutions that deliver real value.
* Adaptability and Curiosity: Stay up-to-date with the latest tools, technologies, and best practices in cloud-based data engineering.
* Detail-Oriented and Quality-Focused: Have a sharp eye for detail and are committed to maintaining high standards for data quality and integrity.
* Team-Oriented Mindset: Thrive in collaborative environments, encouraging diverse perspectives, and fostering a culture of innovation and shared success.