Must Have Technical/Functional Skills 8+ years of data engineering experience, including technical leadership of complex data platforms or pipelines. Demonstrated proficiency processing unstructured and multimodal data, including video, images, LiDAR, GNSS, IMU, and telemetry. Proven experience designing architectures and pipelines for AI training dataset creation at scale. Advanced Python and SQL skills with hands-on experience in distributed processing and workflow orchestration. Experience with cloud data platforms, object storage, lakehouse patterns, metadata, lineage, governance, and dataset versioning. Strong understanding of data quality, observability, performance engineering, and production support. Roles & Responsibilities Own the end-to-end architecture for ingestion, transformation, synchronization, validation, and publishing of multimodal sensor datasets. Define engineering standards, reusable frameworks, data contracts, metadata, lineage, and quality controls. Lead design reviews and guide engineers on implementation, testing, troubleshooting, and performance optimization. Partner with AI, perception, annotation, platform, and business stakeholders to prioritize requirements and milestones. Establish monitoring and operational controls for pipeline reliability, throughput, traceability, and cost. Lead root-cause analysis and remediation for complex data and pipeline defects. Maintain architecture documentation, technical roadmaps, delivery risks, and knowledge transfer. Generic Managerial Skills, If any Technical leadership, work planning, mentoring, stakeholder communication, design governance, risk management, and cross-functional coordination