Description du poste
You will be working on designing and building the geospatial data pipeline that powers our products. As part of our data team you will be heavily involved in our "ground truth," finding and integrating novel datasets, staying ahead of the latest research, and building the high-performance services that bring our map to life. A part of this role also centres on our points-of-interest (POI), geocoding, and search capabilities, the systems that let users find places and turn addresses or names into precise locations. Who we’re looking for As a key member of our early-stage team, you will work across our data stack, from raw data sourcing and processing to the APIs that serve it. Your primary focus will be on building robust, scalable pipelines to ingest, process, and optimize massive geospatial datasets for our applications. You will also stay on the pulse of the latest geospatial research, experiment with new data sources and algorithms, and collaborate directly with the product team to shape our data strategy. What you’ll be doing:
- €¢ Sourcing and integrating foundational datasets from open sources like OpenStreetMap, regional government portals, and commercial providers.
- €¢ Designing and building ETL/ELT pipelines to clean, transform, and load geospatial data into our core database.
- €¢ Optimizing data for performance, including generating vector tiles and structuring data for fast, low-latency queries.
- €¢ Developing and maintaining high-performance APIs in Go to expose our mapping data to our mobile and web applications.
- €¢ Researching and implementing cutting-edge techniques in areas like spatial indexing, routing algorithms, POI/address conflation, and geocoding to make our map smarter.
- €¢ Managing and scaling our geospatial database infrastructure, likely using PostGIS.
- €¢ Collaborating with product and design to understand data requirements and deliver features that delight users.
- €¢ Building and curating our POI dataset; ingesting, deduplicating, and conflating places from multiple sources into a single authoritative record.
- €¢ Designing forward and reverse geocoding pipelines to translate between addresses, place names, and coordinates with high accuracy.
- €¢ Developing search and ranking logic (e.g. autocomplete, fuzzy matching, relevance scoring) to return the right result from a partial or messy query. Requirements:
- €¢ A strong portfolio or GitHub profile showcasing relevant data engineering or backend projects.
- €¢ Deep experience with geospatial databases, particularly PostGIS, and a strong command of spatial SQL.
- €¢ Proficiency in a backend programming language, with a strong preference for Go and Python.
- €¢ Hands-on experience processing large-scale geospatial datasets (e.g., the full OpenStreetMap planet file).
- €¢ Familiarity with geospatial data formats (e.g., GeoJSON, Shapefile, Protobuf) and tooling (GDAL/OGR).
- €¢ Experience with data orchestration (Airflow/Dagster) and cloud infrastructure.
- €¢ Experience building or working with geocoding, address parsing, or place-search systems (e.g. Nominatim, Pelias, Photon, or a bespoke pipeline).
- €¢ Familiarity with full-text/search tooling and relevance ranking (e.g. Elasticsearch/OpenSearch, or PostgreSQL FTS) is a plus. What you can expect:
- €¢ A collaborative and supportive team with short decision-making paths.
- €¢ Exciting and meaningful projects using modern technologies.
- €¢ The opportunity to contribute your ideas and take ownership of your work.
- €¢ Competitive compensation and opportunities for professional growth.
- €¢ A culture that values learning, knowledge sharing, and continuous improvement.
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Détails du poste
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