обновлено 10 часов назад
Senior Data Engineer (Automotive)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Engineer (Automotive): Designing and managing end-to-end data architecture for autonomous systems with an accent on high-bandwidth sensor data ingestion, storage, and retrieval. Focus on building scalable AWS pipelines, defining data schemas, and enabling seamless log-to-replay capabilities for AI and simulation teams.
Location: Belgrade, Serbia; permanent position
Company
develops mmWave radar sensors, perception solutions, and full-stack embedded systems for autonomous systems.
What you will do
- Own end-to-end data architecture for autonomous systems, from edge sensor capture through cloud ingestion, processing, storage, simulation, and model training.
- Define data contracts, schemas, storage strategies, retention policies, and cost-optimization approaches for vehicle and fleet-scale data.
- Design and maintain AWS pipelines for ingesting, processing, indexing, searching, and retrieving multimodal sensor data.
- Develop logging formats and metadata or scenario indexes, while ensuring temporal synchronization, lineage, quality, and observability.
- Partner with AI, Simulation, and Autonomy teams on log-to-replay capabilities for virtual testing, regression validation, and model training.
- Document architectural decisions and mentor engineers on data engineering practices.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
- 5+ years of data engineering experience, including data architecture or technical workstream leadership.
- Deep experience with AWS services including S3, IAM, Lambda, Glue, and Athena.
- Track record building ETL pipelines for unstructured or binary data at scale.
- Strong Python skills and experience with Protobuf, FlatBuffers, or similar serialization formats.
- Understanding of edge-to-cloud communication, bandwidth-constrained uploads, buffering, prioritized data selection, and Linux environments.
Nice to have
- Experience with robotics or automotive sensor data, including ROS2, rosbag2, or MCAP.
- Experience with Foxglove or similar visualization and debugging tools.
- Knowledge of time-series databases and data versioning tools such as DVC or LakeFS.
- AWS or other cloud certifications.
- Experience with data governance or safety-relevant data.
Culture & Benefits
- Ownership of real projects with technical responsibility and autonomy.
- Opportunity to build products and technologies from the ground up.
- Support for professional growth and increased responsibility.
- Collaborative environment where ideas and initiative are encouraged.
- Competitive compensation package with private health insurance.
- Flexible working hours and a relaxed working environment.
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