Ladataan...
EN15.04.2026
Senior Data Engineer
Geospatial
AI ROOTS DATA CASE
We are looking for a Senior Data Engineer for a freelance assignment with a global technology company operating in the Earth observation, geospatial analytics, and risk intelligence domain. The role focuses on building and scaling a high-performance geospatial data platform that enables large-scale analytics across millions of locations.
If you are a senior data engineer with deep expertise in geospatial systems and a passion for building scalable, high-performance data platforms, we would like to hear from you.
If you are a senior data engineer with deep expertise in geospatial systems and a passion for building scalable, high-performance data platforms, we would like to hear from you.
Start
ASAP / as agreed
Duration
7months+
Location
Remote
Allocation
100%
Description
In this role, you will be responsible for evolving an existing geospatial data engine into a continent-scale analytics platform. You will work at the intersection of data engineering, geospatial processing, and performance optimization—building reliable, scalable data structures that power advanced analytics and machine learning use cases.
A key objective is to create an environment where testing new geospatial hypotheses is fast, reliable, and reproducible, and where successful experiments can be seamlessly scaled into production-grade data pipelines.
You will work closely with data scientists and engineers, ensuring frictionless access to high-quality, analysis-ready datasets while maintaining strong data integrity, lineage, and performance standards.
Start date: ASAP or as agreed
Work model: Hybrid: preferred: on-site 3 days per week (Espoo)
Work model: Hybrid: preferred: on-site 3 days per week (Espoo)
Requirements
- Master’s degree in Computer Science, Geoinformatics, or a related quantitative field (or equivalent practical experience)
- 5+ years of professional experience in data engineering, with strong focus on geospatial data
- Proven experience designing and building analysis-ready datasets and data architectures (e.g. feature tables, star schemas, partitioned data formats)
- Strong expertise in PostgreSQL / PostGIS in production environments
- Spatial indexing
- Complex spatial joins
- Performance tuning for large-scale workloads
- Experience working with large-scale geospatial datasets (raster and vector) and understanding performance trade-offs between database-centric and distributed processing
- Strong Python skills and ability to work with complex codebases in production settings
- Hands-on experience with geospatial data formats and tooling, such as:
- Cloud Optimized GeoTIFFs (COGs)
- GeoParquet
- STAC
- Solid understanding of data modeling, transformations, and data lineage, including reprojection and tiling strategies
- Experience with AWS (S3, RDS/Aurora, EC2) and scaling data pipelines in cloud environments
- Experience building reliable, automated data pipelines and workflows (ingestion, orchestration, monitoring)
- Strong focus on data quality, consistency, and observability
- Ability to deliver production-grade, testable, and maintainable code
- Comfortable leveraging AI-assisted development tools (e.g. Cursor, Claude, Copilot)
Nice to have
- Experience with climate, flood, or natural hazard datasets (e.g. FEMA, NOAA, USGS)
- Familiarity with modern geospatial tooling (e.g. GDAL/OGR, rasterio, rioxarray)
- Experience with distributed data platforms (e.g. Databricks, Delta Lake, PySpark, Unity Catalog)
- Experience with Parquet / Arrow for analytical data workflows
- Familiarity with Docker-based development environments and Makefile workflows
Tech Stack
- PostgreSQL / PostGIS
- Python
- GDAL / rasterio
- AWS (S3, RDS/Aurora, EC2)
- Docker
Ota yhteyttä
Kaisaniemenkatu 1 BA, 4. krs00100 Helsinkihello@finitec.fi