CYVL is a Physical AI company building sensors, computer vision, and AI that transform infrastructure data into actionable intelligence. The Data Engineer will build and scale data pipelines and platforms that process LiDAR, imagery, and GPS data into client-ready geospatial deliverables, while improving data quality, workflow automation, and processing performance on AWS.

Responsibilities:

• Design, build, and operate pipelines that move sensor data from ingest to client-ready geospatial outputs
• Build and maintain our data platform so product, AI, and analytics teams can find and use data fast
• Build automated data quality checks and monitoring that catch problems before customers do
• Partner with Data Operations and GIS teams to automate manual workflows and increase throughput
• Improve the cost and performance of processing at scale on AWS

Requirements:

• 3+ years building production data pipelines or data platforms
• Strong Python and SQL
• Experience with cloud data infrastructure (AWS preferred) and workflow orchestration (Airflow, Dagster, Prefect, or similar)
• Experience making large, messy datasets reliable
• Comfort owning systems end to end, from design through on-call
• Geospatial data experience (PostGIS, GDAL, GeoParquet, H3 or other spatial indexing)
• Sensor data: LiDAR point clouds, imagery, GPS/IMU
• Lakehouse formats and engines (Iceberg, Delta, DuckDB, Spark)
• Docker, Kubernetes, and Terraform
• Supporting ML training and inference pipelines