Data Engineer, Application Software

📋 Description

• Build and improve scalable data pipelines that support model development, evaluation, and
• Ingest, transform, and curate large-scale real-world, synthetic, and partner-provided datasets into
• Develop data quality checks, validation processes, and monitoring to ensure both raw data from our
• Curate and mine real-world and synthetic data to drive scenario diversity, coverage, and
• Improve pipeline performance, reliability, and usability, helping reduce bottlenecks and increase
• Collaborate closely with Machine Learning engineers, Data Corpus, AI Platform, and external

🎯 Requirements

• Proven experience building and operating scalable data pipelines or distributed data processing
• Strong software engineering skills in Python, with a solid foundation in maintainable, reliable
• Proficient in SQL and PySpark, with experience using warehouse/OLAP concepts, window functions, and
• Experience with modern data pipeline architectures, including workflow orchestration and DAG-based
• Solid understanding of robotics and automated driving data concepts, including sensor
• Understanding of machine learning development workflows, including training data generation

🎁 Benefits

• Hybrid working policy combining time in office and working from home.
• Core working hours allowing flexible schedules.
• Inclusive interview experience with accommodations available.
• Commitment to diversity, fairness, and respect.