At GM, we’re on a mission to transform the way the world moves. Our Data Engineering team sits at the heart of this mission, building the pipelines and platforms that power next-generation mobility and geospatial services. We have an exciting opportunity for a seasoned Senior Data Engineer who thrives on solving complex challenges, designing scalable solutions, and pushing the boundaries of what’s possible with geospatial and automotive datasets.
In this role, you’ll have the opportunity to design and deliver data pipelines at scale, partner with data engineers and software engineers to bring AI/ML models into production, and lead innovation in big data workflows.
What will you do:
- Design, build, and scale robust data pipelines for large-scale geospatial and automotive datasets.
- Partner with cross-functional teams to prototype and productionize statistical models and AI/ML solutions.
- Optimize workflows for speed, reliability, and scalability across modern big data platforms.
- Evaluate and adopt emerging technologies to push the boundaries of geospatial data processing.
- Translate research prototypes into production-ready systems deployed on leading cloud platforms.
- Champion data quality, validation, and governance at every stage of the pipeline.
- Build resilient infrastructure for data ingestion, transformation, and storage.
- Mentor junior engineers and foster a culture of collaboration, learning, and innovation
Requirements
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related discipline.
- 7+ years’ experience in software engineering with a strong focus on data engineering.
- Proven expertise in Java and Python for data pipeline development.
- Deep knowledge of geospatial data formats (e.g. GeoJSON, Shapefiles) and tools (e.g. ArcGIS, PostGIS).
- Hands-on experience with cloud platforms (Azure preferred; AWS or GCP also considered).
- Strong understanding of relational & non-relational databases, schema design, and data modeling.
- Familiarity with statistical models, feature engineering, and predictive analytics.
- Experience with CI/CD pipelines and DevOps practices.
- Strong analytical, problem-solving, and teamwork skills.
Desirable
- Experience with mapping platforms (HERE, Mapbox, ArcGIS, OpenStreetMap, Google Maps).
- Understanding of vehicle telemetry, mobility data, or location-based services.
- Background in real-time data processing (Kafka, Spark Streaming, Pulsar, Flink).
- Contributions to open-source geospatial or data engineering projects.
Hybrid
This role is categorized as Hybrid. This means the successful candidate is expected to report to the Limerick office 3 times per week, at minimum.
