8 дней назад
Data Engineer, Data Quality & Provenance (Autonomous Driving)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer, Data Quality & Provenance (Autonomous Driving) (Python/SQL, Spark, Airflow): Building scalable batch and streaming pipelines and reproducible datasets for fleet and simulation data with an accent on data quality, lineage, observability, and multimodal data platforms. Focus on designing distributed storage and compute workflows, creating discoverable data products, and enabling ML, autonomy, simulation, and safety analysis at petabyte scale.
Location: Hybrid role based in the office in Leonberg, Germany, with time spent working from home
Company
develops autonomous-driving technology powered by fleet and simulation data.
What you will do
- Design, build, and operate scalable batch and streaming pipelines for multimodal fleet and simulation data.
- Create data models, catalogs, indexes, and query capabilities for sensor, vehicle-state, map, and event data.
- Build versioned and reproducible datasets for training, evaluation, replay, scenario mining, and safety analysis.
- Develop workflows for data ingestion, synchronization, transformation, curation, labeling, and data-quality validation.
- Partner with autonomy, ML, simulation, and safety engineers to define schemas, APIs, and data contracts.
- Establish standards for lineage, observability, access controls, retention, cost management, reliability, and performance.
Requirements
- Strong hands-on Python and SQL skills with solid production software-engineering fundamentals.
- Experience designing and operating large-scale distributed data systems and cloud-based data platforms using object storage.
- Hands-on experience with distributed processing and workflow orchestration technologies such as Spark, Flyte, Airflow, or equivalent tools.
- Experience owning data quality, lineage, observability, reproducibility, and incident response for production workflows.
- Ability to translate ambiguous requirements from ML, data-science, robotics, or similarly technical teams into reusable platform capabilities.
- Ability to work in a hybrid arrangement based in Leonberg, Germany.
Nice to have
- Experience in autonomous vehicles, ADAS, robotics, mapping, drones, or another sensor-rich domain.
- Familiarity with time-synchronized sensor data, geospatial data, or multimodal datasets.
- Understanding of ML training, evaluation, simulation, or closed-loop development workflows.
Culture & Benefits
- Full-time position combining office and workshop collaboration with working from home.
- Office-based time supports innovation, culture, relationships, and learning.
- Work on autonomous-driving data infrastructure at petabyte scale.
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