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Senior Data Engineer (Autonomous Driving)

indrive

Senior 🇬🇧 English
Python SQL AWS GCP Docker Kubernetes PostGIS GeoPandas Shapely BigQuery Spark S3 GCS ROS2 bag Parquet Iceberg Airflow QGIS

Job description

About the role

Indrive is building the data foundation for its autonomous-driving work and is hiring the engineer who will start it. Today the company collects street-level imagery and GPS tracks from vehicle cameras, including its own camera units with NVIDIA edge devices, to update maps. When a dedicated survey vehicle with a full sensor set (multi-camera, IMU, LiDAR) arrives, you will build the pipelines that turn its data into training datasets for autonomous-driving models.

Key responsibilities

  • Build pipelines that move multi-sensor data (multi-camera video, IMU, LiDAR, GPS) from vehicles into cloud storage, synchronizing and geo-referencing the streams
  • Own the storage layout and lifecycle for sensor data: partitioning, hot and archival tiers, and cost control as volume grows
  • Set up validation and monitoring on the ingest path: incomplete uploads, missing or unsynchronized streams, and vehicles that stop producing usable data
  • Prepare training datasets for autonomous-driving models: select data by location, route and conditions, version datasets and deliver them in the formats ML teams need
  • Take over and develop the current imagery and GPS-track pipelines from vehicle cameras, and contribute to geodata pipelines (ingestion from company data, OpenStreetMap, Overture Maps and vendors, conflation, validation, publication)
  • Work with company data in BigQuery and keep spatial queries fast on large PostGIS and GeoParquet tables

Required profile

  • 4+ years in data engineering
  • Experience with multi-sensor data from vehicles or robots (cameras, IMU, LiDAR) and keeping the streams in sync
  • Experience preparing training datasets for computer vision or autonomous-driving models
  • Experience handling large volumes of binary or media data in object storage and distributed processing
  • Hands-on experience with spatial data: PostGIS, GeoPandas/Shapely, coordinate reference systems and GPS tracks

Required skills

  • Strong Python and SQL
  • AWS or GCP, Docker, Kubernetes
  • Nice to have: ROS2 bag, MCAP or point clouds; Parquet, Delta or Iceberg; Databricks; Argo Workflows or Airflow; OpenStreetMap and Overture Maps; QGIS; BigQuery

What we offer

  • Mentoring, career consulting and learning programs
  • International experience through the Global Talent Exchange Program
  • Company-wide challenges, awards, sports, social impact and volunteering projects
  • Co-financed language courses and internal speaking clubs

Questions fréquentes

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Source : ats:pinpoint

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Published 1 week ago

Expires 1 month from now

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