Geospatial Analytics Engineer
PathGen turns pathogen sequence data into decision support for public health teams — without the genomes ever leaving the country that holds them.
- Location
- Singapore
- Work type
- Hybrid
- Schedule
- Full-time
- Status
- Open
Role Overview:
Build and develop a containerized geospatial analytics platform combining an interactive web UI, a Python analytics API backed by an analytical database (DuckDB), and raster tile services for Cloud Optimized GeoTIFF (COG) datasets. You will work closely with data engineers and full-stack developers to develop our geospatial system end-to-end: data pipelines, geospatial correctness, performance, and user-facing workflows.
Responsibilities:
- Deliver features end-to-end across UI, APIs, and geospatial services.
- Design and optimize analytical schemas and SQL (DuckDB) for performance.
- Implement real-time query and data delivery via WebSockets/streaming (Arrow/JSON) plus REST endpoints for metadata and access.
- Build interactive, map-centric dashboards (choropleths, markers, filters) with correct geospatial interpretation and responsive UI.
- Build coordinated, interactive analytics so actions in one view (map, chart, or layer) update all others.
- Optimize coordinated query execution across heterogeneous data sources (DuckDB spatial queries, TiTiler raster requests, vector tile services).
- Improve performance and reliability through profiling, caching, defensive data handling, and sane defaults.
- Strengthen developer experience via reproducible Docker workflows and robust automated testing.
Essential Qualifications:
- Strong TypeScript + React experience building map-driven SPAs.
- Strong Python backend engineering (async APIs, WebSockets, streaming responses).
- Strong SQL and analytical mindset; familiarity with columnar/Arrow-style data exchange.
- Solid geospatial fundamentals: vector/raster data, coordinate systems, Web Mercator tiling.
- Experience building reactive data architectures with centralized state coordination (e.g., Mosaic, Observable Plot, or similar frameworks).
- Expertise in geospatial query optimization across both vector (DuckDB/PostGIS) and raster (COG/TiTiler) data sources.
- Practical experience with COGs and raster tooling (e.g., rasterio, rio-tiler, TiTiler-like systems).
- Comfort with containerized, multi-service development and E2E testing (Playwright or equivalent).
Bonus Qualifications:
- AWS data delivery patterns (S3, IAM, CDN/CloudFront) and cost and performance trade-offs.
- Advanced geospatial concepts (STAC, PostGIS, vector tiles, raster statistics).
- Observability for multi-service systems (logging, metrics, tracing).
- Familiarity with LLM-assisted data tooling or agent-style workflows, with safety and evaluation in mind.
Desired Personal Attributes:
- Start-up mentality (flexible & pragmatic)
- Strong collaboration skills in multi-disciplinary environments.
- Systems thinking and a bias toward reliability & scalability.
- Ability to design practical, maintainable geospatial & analytics infrastructure.
What We Offer:
- A mission-driven environment focused on improving global public health.
- Opportunities to work on high-impact problems in AI and pathogen genomics.
- A flexible and collaborative work culture with a commitment to innovation.
- Low bureaucracy with direct ownership of the product — no ticket-factory work.
- Competitive salary and paid leave.
- Hybrid-friendly work pattern.
Join us to help operationalize the future of genomic intelligence and deploy real-world AI tools that matter.
Apply
Send a CV and a short note on the work you want to do. Applications for this role go to [email protected].