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Path Robotics is building embodied AI systems that enable robots to adapt, learn, and perform in the real world. The company combines perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world deployment.
You will play a mission-critical role architecting the data platform that enables machine learning and robotics teams to move faster, experiment more effectively, and deploy AI solutions into production. Reporting to the Data Engineering Manager, you will collaborate with data engineers, ML engineers, and software engineers to deliver clean, reliable, and scalable data products.
Key responsibilities include:
- Partner with software, ML, robotics, and analytics teams to understand data needs and translate them into well-modeled tables and data products
- Develop and extend data models and pipeline assets supporting experimentation, model training and validation, reporting, and business decisions
- Model large-scale, multi-modal data including sensor streams, application telemetry, system logs, and unstructured blob data
- Monitor pipeline health and data quality, troubleshoot failures, and improve tests and alerting to build trust in data assets
- Apply and strengthen team standards for governance, lineage, documentation, and data contracts
- Write clean, tested, well-documented Python and SQL code and participate in team code reviews
- Improve the data platform's usability, performance, and tooling, and evangelize enhancements to users
Requirements:
- 2+ years of experience in data engineering or closely related role, building and supporting production data pipelines
- Strong proficiency in SQL and Python
- Hands-on experience with tools like AWS, Snowflake, Dagster, dbt, or equivalent modern data stack
- Solid grasp of data modeling, warehousing concepts, and pipeline orchestration
- Curious about the problems your data solves; enjoy working directly with stakeholders to deliver data that drives real decisions
- Take ownership of work, communicate clearly, and want to learn from and contribute to an experienced team
- Bonus: experience working with sensor data, robotics logs, manipulation data, or other high-volume, real-world datasets
