About the Role

GenAirate Technologies builds Atlas, a geospatial commercial property risk intelligence platform for insurance underwriters, and SnapLine, an AI-powered submission intelligence platform for the London Market and US specialty insurance.

Atlas pulls together data from a wide range of sources, including FEMA, NOAA, USGS, USACE, parcel records, aerial imagery vendors, and licensed geospatial datasets, and turns it into structured risk layers underwriters can actually use (flood protection, fire protection, GL insights, site access, coastline distance, and more). We're looking for a Data Engineer to own this pipeline end to end: sourcing, ingesting, cleaning, and structuring the data that powers Atlas.

What You'll Do

- Identify, evaluate, and integrate new geospatial and risk-relevant data sources (government, commercial, licensed)
- Build and maintain ingestion pipelines that handle a mix of structured and unstructured data, from shapefiles and GeoTIFFs to APIs and scraped datasets
- Design data schemas for recent risk layers (you'll work directly on things like GL insights and flood protection schemas)
- Own data quality: validation, deduplication, parcel stitching, and geocoding accuracy
- Navigate licensing and usage restrictions across data vendors and ensure pipelines stay compliant (this matters a lot,



some of our sources have strict terms on model training and redistribution)

What We're Looking For

- 2 to 4 years of experience as a data engineer, ideally with some exposure to geospatial data (GIS, satellite imagery, parcel data, or similar)
- Strong SQL and Python, comfort with data pipeline tools (Airflow or similar)
- Experience working with cloud data infrastructure (AWS or GCP), including storage and processing at scale
- Ability to read and reason about data licensing terms, and flag risk before it becomes a problem
- Comfortable working with messy, inconsistent, real-world data from multiple external sources
- Good judgment on data quality tradeoffs; you know when something is good enough to ship and when it isn't

Bonus Points

- Experience with satellite or aerial imagery pipelines (Airbus, Vexcel, Nearmap, EagleView, or similar)
- Familiarity with insurance, property risk, or catastrophe modeling concepts
- Experience with vector databases or spatial indexing

What We're Not Looking For

- Candidates who only want to work with clean, well-documented internal data. Most of what this role touches comes from external sources with inconsistent formats, unclear documentation, and real licensing constraints. You need to be comfortable figuring things out.

📌 Data Engineer (Bengaluru)
🏢 GenAirate Technologies
📍 Bengaluru