Data Engineer
On-site · San Francisco, California, United States
Job Summary
Data Engineer to transform large-scale geospatial datasets into structured, reliable formats for ML and production pipelines. Own ingestion, standardization, storage, and accessibility of point cloud, imagery, and geospatial data to support training, perception, and visualization. Build scalable workflows for ingesting and processing diverse data sources, convert sensor datasets into standardized internal formats, and develop CI/CD pipelines with automated checks. Optimize processing performance, query speed, and storage efficiency, and collaborate with customer success, ML, and product teams to unblock customer projects. Build and maintain agentic harnesses to automate data triage and code patching, and facilitate data integration with data-provider partners (occasional travel). Excellent problem-solving, Python development, and distributed-systems skills are essential.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, or equivalent experience
- Strong software development and debugging skills with hands-on experience building production systems in Python
- Solid foundation in distributed systems and parallel computing
- Comfort operating with ambiguity and reverse-engineering undocumented data formats
- Experience building agentic systems and setting up agent harnesses for triage, debugging, or automated code patching
- Strong communication and collaboration skills across ML, product, and customer-facing teams
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