Ford Motor Company is dedicated to transforming the future of transportation through its Electric Vehicles, Digital and Design team. As a Telematics Data Engineer, you will build and maintain scalable data pipelines to process vehicle telemetry and geospatial data, ensuring high-quality data assets for analytics.
Responsibilities:
- Develop Telematics Pipelines: Build and operate end-to-end data pipelines (ETL/ELT) that ingest and process large-scale vehicle telemetry, including GPS, speed, and engine diagnostics
- Integrate Map APIs: Implement and maintain integrations with Google Maps APIs for geocoding, snap-to-road functionality, and distance calculations
- Spatial Data Modeling: Develop and optimize data models in BigQuery using GEOGRAPHY types and spatial indexing (e.g., S2 or H3 cells) for efficient geospatial querying
- Medallion Architecture: Maintain data flowing through Bronze, Silver, and Gold layers to support trip reconstruction and reporting
- Orchestration & CI/CD: Build and manage pipeline orchestration using Airflow/Astronomer and ensure deployments follow CI/CD standards using Terraform and Git
- Monitor Data Quality: Implement automated checks to detect GPS drift, signal loss, or data inconsistencies using tools like Splunk, Grafana, or Looker
- Privacy & Security: Apply data governance and compliance controls, ensuring the protection of sensitive location data and PII
- Cloud Optimization: Monitor GCP resource usage (BigQuery, Dataflow, GCS) to ensure cost-effective processing of high-frequency telematics data
- Support & Maintenance: Participate in on-call rotations and incident response to maintain the reliability of data services
Requirements:
- Bachelor's in Computer Science, Information Systems, or a related field
- 3+ years of experience in data engineering or a similar technical role and direct experience in telemetry, IoT, or time-series data
- 3+ years Google Cloud Platform (BigQuery, Cloud Storage, Dataflow, Dataproc)
- 1+ year experience working with Google Maps Platform APIs or similar geospatial web services
- Strong proficiency in Python and SQL; experience with PySpark and geospatial libraries (e.g., GeoPandas, Shapely)