Data engineer (Geospatial)
Summary
A full-time data engineering role at a consulting/technology services firm in Bangalore, deploying on a project for a leading US oil & gas client. The engineer builds and owns production ETL pipelines and architecture using Python, SQL, and Spark/PySpark, with mandatory hands-on geospatial dataset experience and large-scale processing on any major cloud.
Company Overview
A global consulting and technology services firm focused on helping organizations drive business excellence through digital transformation, data & AI, enterprise architecture, managed services, and sustainability/ESG initiatives.
The company combines business strategy consulting with engineering and technology delivery, enabling organizations to modernize operations, leverage data-driven insights, and build sustainable business solutions.
Join the organization to work on diverse, high-impact digital and AI transformation projects as part of a global, growth-focused team.
Employment & Project:
This is a full-time opportunity with the organization, where you will be deployed on a project with a leading US-based organization in the oil & gas industry.
Role overview:
5-10 Years of Experience
- Core Data Engineering: 5–10 years with strong hands-on Python, SQL, Spark/PySpark and production ETL/data pipelines.
- Geospatial – Mandatory: Genuine experience working with geospatial/location datasets — coordinates, latitude/longitude, GPS, maps, satellite imagery, spatial datasets, etc.
- End-to-End Pipeline Ownership: Should have experience designing/building scalable data pipelines and architecture, including orchestration, data processing, storage and production support.
- Cloud & Scale: Any cloud (AWS/Azure/GCP) is acceptable, but should have hands-on experience processing large-scale data using cloud/data-platform technologies.
- Hands-on + Production Mindset: Looking for someone who remains technically hands-on and has experience with monitoring, data quality, troubleshooting, optimisation and production deployments.