September 18, 2024
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Berlin, Berlin, Germany, Germany
September 18, 2024
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Your mission
- Develop, optimize, and maintain scalable data pipelines and architectures.
- Build and implement ETL processes for integrating and processing large volumes of data from varioussources.
- Collaborate closely with developers and data scientists to develop, integrate, and optimize machine learning models. Actively participate in selecting suitable ML frameworks and tools (e.g., TensorFlow, PyTorch).
- Design and maintain databases and data warehouses to ensure efficient storage and processing of large data sets.
- Independently lead data-driven projects, including coordinating and communicating with variousstakeholders, defining project requirements, and ensuring timely delivery.
- Optimize data infrastructure for performance, security, and scalability.
- Ensure data quality by implementing monitoring and testing mechanisms.
- Support in selecting and implementing appropriate tools and technologies (e.g., cloud data platforms like AWS Redshift, Google BigQuery, and Azure Synapse Analytics).
- Bachelor's degree in computer science, Data Science, Engineering, or a comparable qualification.
- Several years of professional experience as a Data Engineer, ideally in a consulting environment or digital field.
- In-depth knowledge of developing and maintaining data pipelines.
- Extensive experience with relational and NoSQL databases (e.g., SQL, PostgreSQL, MongoDB) and clouddata platforms (AWS, Google Cloud, Azure).
- Experience working with Big Data technologies (e.g., Hadoop, Spark) as well as specific tools like Apache Kafka and Airflow.
- Programming skills in Python, Java, or Scala.
- Experience using cloud data platforms like AWS Redshift, Google BigQuery, and Azure Synapse Analytics.
- Analytical thinking, problem-solving skills, and the ability to communicate complex technical issues.
- Business fluent in German and English, both written and spoken.
