Our client is looking for a Ukraine-based specialist to join a client engineering team as an embedded contractor. The role sits at the intersection of geospatial analysis and applied data engineering: building spatial data models and pipelines in Python, and supporting the cloud and streaming infrastructure those pipelines run on. This is a hands-on build role, not a research or academic position.
What You Will Work On
Design and build geospatial data models and analytical pipelines using Python, applying spatial mathematics (coordinate systems, spatial statistics, geometric and network analysis) to real production data.
Develop and maintain data pipelines that ingest, transform, and serve geospatial and streaming data at scale.
Contribute to AWS architecture decisions for the data and analytics workloads this role owns, including compute, storage, and pipeline orchestration.
Build and support Kafka-based streaming components where geospatial or event data needs to move in near real time.
Support blockchain-related data workflows, such as ingesting or validating on-chain data as part of a broader data science pipeline.
Work as a full member of the client's engineering team: standups, code review, sprint planning, shared ownership of outcomes.
Must-Have
Strong applied mathematics background in geospatial analysis, geodesy, or spatial statistics, demonstrated through work, not only coursework.
Professional Python development experience, including data pipeline or data engineering work (not only notebooks/analysis scripts).
Practical, hands-on AWS experience: has designed or significantly contributed to cloud architecture for a data or analytics workload, not only used managed services as an end user.
Nice to have
AWS Solutions Architect certification (Associate or Professional).
Production experience with Kafka or another streaming/event platform.
Experience with blockchain data: on-chain data extraction, validation, or analytics.
Familiarity with geospatial libraries and tooling (GeoPandas, Shapely, Rasterio, PostGIS, or similar).
Experience with satellite imagery or remote sensing data.
