Data Engineer (m/f/d)
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Key skills for this role
About the Role
Halian is seeking a Data Engineer to design and build scalable data infrastructure for autonomous systems in Abu Dhabi. The role involves transforming large-scale multimodal sensor data into high-quality datasets for machine learning.
Key Skills for This Role
Responsibilities
- Design and manage high throughput on vehicle data recording pipelines
- Design and maintain scalable data lake architecture across S3, FSx/Lustre, and GCS
- Build dataset pipelines converting raw sensor data into structured, training ready datasets
- Implement robust dataset versioning and discovery processes
- Contribute to defining efficient on disk dataset formats
- Develop and manage annotation pipelines, including vendor handoff and quality control
Requirements
- 5+ years of experience building production grade data infrastructure, ideally involving large scale multimodal or sensor data
- Strong proficiency in Python
- Ability to work with C++ for ROS2 and pipeline related tooling
- Hands on experience with cloud storage and distributed systems (S3, GCS, FSx, Lustre)
- Experience with dataset versioning and ML data tools such as DVC, LakeFS, Deep Lake, FiftyOne
Full Job Posting
Role Overview
- Design and build scalable data infrastructure to support advanced autonomous systems.
- Transform large scale multimodal sensor data into high quality, structured datasets for machine learning.
- Establish foundational systems and architectural decisions for long term scalability.
Key Responsibilities
- On vehicle data recording pipeline: design and manage high throughput recording systems, including topic selection, multi GB/s write pipelines, and efficient data formats (MCAP/rosbag2).
- Data lake architecture: design and maintain scalable storage solutions across S3, FSx/Lustre, and GCS.
- Dataset pipeline development: build pipelines that convert raw sensor data into structured, training ready datasets.
- Versioning and dataset management: implement robust dataset versioning and discovery processes using tools like DVC, LakeFS, Deep Lake, and FiftyOne.
- Dataset format design: contribute to defining efficient on disk dataset formats for large scale training.
- Annotation workflows: develop and manage annotation pipelines, including vendor handoff, quality control, and schema evolution.
Required Experience
- 5+ years of experience building production grade data infrastructure, ideally involving large scale multimodal or sensor data.
- Strong proficiency in Python, with ability to work with C++ for ROS2 and pipeline related tooling.
- Hands on experience with cloud storage and distributed systems (S3, GCS, FSx, Lustre), including performance and cost optimization.
- Experience with dataset versioning and ML data tools such as DVC, LakeFS, Deep Lake, FiftyOne, or similar platforms.
Preferred Qualifications
- Background in autonomous systems or mobile platforms, particularly in complex or unstructured environments.
- Experience working with large scale annotation workflows and external labeling providers.
- Familiarity with distributed training approaches (e.g., DDP, FSDP) to support efficient collaboration with machine learning infrastructure.
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