Note: The job is a remote job and is open to candidates in USA. Covetus is hiring a Data Engineer to build and maintain scalable pipelines for multimodal manufacturing data. The role prepares curated datasets for annotation and AI training while ensuring data quality, consistency, reliability, and effective collaboration across teams.
Responsibilities
- Design, develop, and maintain scalable pipelines for camera, LiDAR, GNSS, IMU, and telemetry data
- Normalize, synchronize, enrich, and package multimodal data for annotation and AI training
- Implement automated checks for completeness, integrity, calibration, timestamps, formats, and dataset consistency
- Create reusable data models, metadata standards, lineage, and dataset-versioning practices
- Optimize pipeline performance, reliability, observability, and cost
- Troubleshoot data defects and collaborate with AI, annotation, quality, and platform teams
- Document technical designs, operating procedures, and handoffs
Skills
- Only USC and GC
- With Manufacturing or engineering client experience
- 5+ years of data engineering experience
- Demonstrated experience processing unstructured and multimodal data, including video, images, LiDAR, GNSS, IMU, and telemetry
- Experience building pipelines that create curated AI training datasets through ingestion, synchronization, transformation, validation, and publishing
- Strong Python and SQL skills with experience in distributed data processing frameworks
- Experience with cloud data platforms, object storage, data lake or lakehouse patterns, workflow orchestration, and version control
- Knowledge of data quality, metadata, lineage, schema management, and reproducible dataset pipelines
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