Senior Data Engineer (m/w/d)

As a Senior Data Engineer, you will play a key role in managing, integrating, and optimizing data across Upstream and Downstream activities, with a particular focus on data used for forecasting purposes.

You will be responsible for ensuring data quality, consistency, and accessibility across multiple sources, enabling efficient use by business stakeholders, Data Analysts, and Data Scientists. You will contribute to data governance initiatives, support architectural decisions, and implement best practices in data management.

Data Engineering & Data Management:

• Capture, integrate, and process structured and unstructured data from various internal and external sources.
• Design, develop, and maintain robust ETL/ELT pipelines.
• Structure, standardize, qualify, and document data to ensure consistency and usability.
• Map and maintain data lineage and data source documentation.
• Monitor and improve data quality through validation, testing, and cleansing processes.
• Identify and eliminate duplicate, incomplete, or inconsistent data.
• Ensure the quality and reliability of data entering the Data Lake.
• Contribute to the creation and maintenance of data repositories when required.
• Promote and implement best practices in data governance and data management.

Development & Architecture:

• Develop solutions within the enterprise data framework.
• Write technical specifications and design documentation.
• Develop and execute unit tests to ensure solution reliability.
• Participate in technical and architectural discussions and contribute to strategic data platform decisions.
• Support the continuous improvement of data architecture and engineering practices.
• Ensure timely delivery of development activities while maintaining high-quality standards.

Operations & Support:

• Monitor production systems and data pipelines.
• Perform maintenance, troubleshooting, and issue resolution.
• Ensure operational stability and performance of data processing environments.
• Collaborate closely with business stakeholders, architects, developers, Data Analysts, and Data Scientists.

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.
• Strong experience in Python development for data processing, scripting, and ETL implementation.
• Advanced knowledge of SQL, relational databases, and data warehouse concepts.
• Experience designing and optimizing data models and database performance.
• Strong understanding of software development best practices.