inDrive

Global ride-hailing platform with fare negotiation

Senior Data Engineer

Data EngineeringUpdated on Nov 13

Full-timeAbu Dhabi - United Arab EmiratesNo salary listedHybrid

About the Job

Requirements

At least 4 years of experience in data engineering.
Experience with multi-sensor data from vehicles or robots, including cameras, IMU, or LiDAR, and synchronizing streams.
Experience preparing training datasets for computer vision or autonomous-driving models.
Experience handling large volumes of binary or media data in object storage such as S3 or GCS, and using distributed processing such as Spark or an equivalent.
Hands-on experience with spatial data, including PostGIS, GeoPandas or Shapely, coordinate reference systems, and GPS tracks.
Strong Python and SQL skills, with AWS or GCP, Docker, and Kubernetes.

Responsibilities

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

Desired Qualifications

Experience with sensor-data formats such as ROS2 bag, MCAP, or point clouds.
Experience with Parquet, Delta, or Iceberg, and Databricks.
Experience with Argo Workflows or Airflow.
Experience with OpenStreetMap and Overture Map.
Experience with QGIS.
Experience with BigQuery.

About the role
We are preparing the data foundation for our autonomous-driving work, and we are hiring the engineer who will start it. Today we collect street-level imagery and GPS tracks from vehicle cameras, including our own camera units with NVIDIA edge devices on board, and use them to update maps. Next comes a dedicated survey vehicle with a full sensor set: multi-camera, IMU, LiDAR. You will start with the imagery and map data pipelines we run today, and as the sensor platform arrives, you will build the pipelines that turn its data into training datasets for autonomous-driving models.

Build the pipelines that move multi-sensor data (multi-camera video, IMU, LiDAR, GPS) from vehicles into cloud storage, synchronize and geo-reference the streams
Own the storage layout and lifecycle for sensor data: partitioning, hot and archival tiers, cost control as volume grows
Build validation and monitoring on the ingest path: incomplete uploads, missing or unsynchronized streams, vehicles that stopped 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
Until then: 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

4+ years in data engineering
Experience with multi-sensor data from vehicles or robots: cameras, IMU or LiDAR, and keeping the streams in sync
Experience preparing training datasets for computer vision or autonomous-driving models.
Large volumes of binary or media data in object storage (S3 or GCS); distributed processing (Spark or equivalent)
Hands-on experience with spatial data: PostGIS, GeoPandas/Shapely, coordinate reference systems, GPS tracks
Strong Python and SQL; AWS or GCP, Docker, Kubernetes

Nice to have

Sensor data formats such as ROS2 bag, MCAP or point clouds
Parquet, Delta or Iceberg; Databricks
Argo Workflows or Airflow
OpenStreetMap and Overture Map
QGIS
BigQuery

About the Company

inDrive

Global ride-hailing platform with fare negotiation

inDrive operates a global mobility and urban services platform that connects passengers with independent drivers through a fare-negotiation system. Riders propose a trip price, and nearby drivers can accept, decline, or counteroffer, creating a peer-to-peer ride-hailing model. The service has expanded to intercity rides, delivery and cargo, groceries, advertising, and driver-focused fintech within its app. Unlike typical ride-hailing apps that use fixed fares, inDrive enables price negotiation and direct driver-rider interaction, and it pursues growth through a venture arm that funds ride-hailing-adjacent startups in emerging markets. This broader strategy aims to build a super-app for urban and gig-economy needs, with the goal of offering a wide range of mobility and urban services in 48 countries.

Company size: 10,001+
Company stage: Debt Financing
Total funding: $532M
Headquarters: Mountain View, CA
Founded: 2012

Recently Posted Jobs

Explore more opportunities at inDrive

See more jobs