data engineer

The company develops AI-driven solutions for the agricultural sector, focusing on geospatial, time-series, and analytical data processing.

• Design scalable data architectures for OLTP, OLAP, batch, and near real-time workloads;
• Build and maintain ETL/ELT pipelines using Apache Airflow and streaming pipelines with Apache Kafka;
• Design and optimize PostgreSQL/PostGIS and TimescaleDB databases;
• Manage geospatial, remote sensing, and time-series datasets, including raster, vector, STAC, and Parquet-based storage;
• Support distributed data processing with Apache Spark;
• Implement monitoring, data quality, and production reliability practices;
• Collaborate closely with GIS, AI, backend, and data science teams.

• 3+ Years of experience building production-grade data platforms;
• Strong expertise in Python, SQL, PostgreSQL/PostGIS, and Apache Airflow;
• Experience with Kafka, TimescaleDB, MinIO (or similar object storage), and containerized environments;
• Solid understanding of geospatial data, spatial indexing, and coordinate systems;
• Experience with Linux, Docker, and scalable system design;
• Nice to have: Apache Spark, STAC catalogs, remote sensing and Earth Observation data, GDAL, Rasterio, GeoPandas, Kubernetes, Grafana, Prometheus, Data Lakehouse architectures, cloud infrastructure, AI/ML data pipelines, feature stores, metadata management, and agricultural, climate, or environmental datasets.

• No conditions specified