Data Engineer
About the role
- 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.
- 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.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
