DataEngineer

THE ROLE We're seeking a Data Engineer to transform large-scale geospatial datasets into structured, reliable, and accessible formats that power Mach9's ML and product pipelines. You'll work with high-volume data sources — laser scan point clouds, imagery, and a long tail of geospatial formats — and own the systems that get them ingested, standardized, stored, and made available for training, perception, and production use in a consistent and efficient way. This role sits at the front of everything we do: our models are only as good as the data feeding them, and you'll be the one making that data trustworthy at scale. RESPONSIBILITIES - Develop and maintain scalable, reproducible workflows for ingesting and processing large volumes of point cloud, imagery, and geospatial data. - Convert datasets from various sensor providers into Mach9's standardized internal formats. - Build CI/CD pipelines and automated checks that guarantee the correctness and consistency of data pipelines, including regression detection on dataset processing. - Optimize processing performance, query speed, and storage efficiency across large geospatial datasets. - Work closely with the customer success team to efficiently resolve issues and unblock customer projects. - Build and maintain agentic harness for automated dataset triage and code patching. Automatically propose or apply fixes, and escalate when human judgment is needed. - Work closely with ML and product teams to make data readily usable for training, inference and visualization. - Work closely with customers and data-provider partners to facilitate data integration (with occasional travels). - Puzzle-hunting: work with data formats with sparse or missing documentation. REQUIREMENTS - Strong software development, problem-solving, and debugging skills, with hands-on experience building production systems in Python. - Solid foundation in distributed systems and parallel computing. - Comfort operating with ambiguity — able to dig into un