<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <p>We are looking for a high-performing <strong>Data Engineer</strong> to build the backbone of our AI and Machine Learning workloads. You won't just be moving data; you’ll be architecting the systems that power our next generation of intelligence.</p><strong>The Role</strong><p>As a core member of our engineering team, you will design and implement the ETL/ELT pipelines that feed our ML models. You’ll bridge the gap between raw data and actionable AI, ensuring high-speed delivery, impeccable data quality, and robust infrastructure.</p><p><strong>Key Responsibilities:</strong></p><ul><li><strong>Pipeline Architecture:</strong> Design/implement ETL/ELT for structured and unstructured data.</li><li><strong>AI Support:</strong> Build and maintain data infrastructure specifically for ML/AI workloads.</li><li><strong>Reliability:</strong> Implement rigorous data quality checks, monitoring, and alerting.</li><li><strong>Storage Management:</strong> Manage and optimize Data Warehouse and Data Lake architectures.</li><li><strong>Processing:</strong> Handle both high-velocity streaming and large-scale batch processing.</li><li><strong>Collaboration:</strong> Work closely with MLOps and AI Engineering to ensure seamless data availability.</li></ul><strong>Your Profile</strong><p><strong>The Essentials (Must-Haves):</strong></p><ul><li><strong>Language:</strong> Native or C1-level German (Mandatory).</li><li><strong>Core Tech:</strong> Expert-level Python and Advanced SQL.</li><li><strong>Big Data:</strong> Proficiency in Apache Spark and/or PySpark.</li><li><strong>Cloud:</strong> Proven experience in AWS, Azure, or GCP.</li><li><strong>Orchestration:</strong> Hands-on with Apache Airflow (or equivalent).</li></ul><p><strong>The "Stand-Out" Skills:</strong> We are particularly interested in candidates with experience in high-performance data tools:</p><ul><li><strong>Ray, Apache Iceberg, Apache Arrow, and Polars.</strong></li></ul><strong>Specific Experience Requirements</strong><p><em>This role requires a documented track record of success:</em></p><ul><li><strong>2–5 completed Data Engineering projects</strong> within the last 3 years.</li><li><strong>Scale:</strong> Total project volume of at least <strong>200 person-days</strong> (minimum 20 days per project).</li><li><strong>Verification:</strong> You must be able to provide <strong>2 signed letters of reference</strong> and client-signed project completions.</li></ul><p><br/></p> </div>