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Data Infrastructure Engineer (DBA & Data Engineering)

Listed by ISI - ImageSat International

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Description

ImageSat International (ISI) combines advanced earth observation satellites, space and ground infrastructure, and AI-driven analytics to deliver geospatial intelligence. We're looking for a hands-on Data Infrastructure Engineer to join our team! The role combines database administration, data engineering, and large-scale data processing across cloud and on-premises environments, focusing on geospatial data, satellite imagery, and metadata. Requirements: B.Sc. in Computer Science, Software Engineering, Information Systems, Geoinformatics, or a related field, or equivalent practical experience. 5+ years of experience in DBA and/or Data Engineering, including production systems across cloud and on-premises environments. 2+ years of experience with geospatial data and/or large image datasets. Strong SQL and Python skills. Hands-on experience with PostgreSQL/PostGIS and spatial data. Experience with ETL/ELT pipelines, streaming technologies (e.g., Kafka), and CDC (e.g., Debezium). Experience with Data Catalog and Data Lineage tools. Experience with Apache Spark or similar frameworks and object storage. Production database experience, including security, backup, restore, high availability, and troubleshooting. Ability to work independently and collaborate across teams. Responsibilities: Design, implement, and maintain data infrastructure across cloud and on-premises environments. Manage production databases, including security, monitoring, backups, recovery, and performance optimization. Develop ETL/ELT pipelines, streaming processes, and data synchronization. Process and manage geospatial data, satellite imagery, and metadata. Ensure data quality, availability, and scalability while collaborating with technical teams. Advantages: Experience with GIS tools (GDAL/OGR, Rasterio, GeoPandas, QGIS, ArcGIS, GeoServer) and geospatial formats (COG, STAC, GeoParquet, Zarr). Experience with Airflow, Kubernetes, Infrastructure as Code, and CI/CD. Experience with AWS, Azure, or GCP data services. Knowledge of Data Lakes and formats such as Parquet, Iceberg, or Delta. Experience with satellite or aerial imagery and large scientific datasets.

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