Job Description

We are looking for a highly analytical data engineer who can design and implement complex SQL and PySpark logic over massive, high-frequency time-series data from real-world vehicle sensor recordings. This role requires the ability to craft intricate temporal and spatial query logic—including multi-table joins, windowing across time, and event-detection rules—to extract meaningful driving behaviors from a rich 3D world-model (obstacles, lanes, traffic signs, etc.). The ideal candidate excels at breaking down complex behavioral patterns into precise, scalable query logic and optimizing these queries to run efficiently on large datasets. We are also looking for someone who can work independently.

Project Description

This long-term engagement supports simulation data processing for Autonomous Vehicle (AV) development. Key scenarios include obstacle detection, path planning, and complex traffic situations (e.g., tunnels, unusual vehicles, or temporary network issues). The ...

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