DevJobs

Data Infrastructure Engineer (DBA & Data Engineering)

Overview
Skills
  • SQL SQL
  • Python Python
  • Kafka Kafka
  • PostgreSQL PostgreSQL
  • CI/CD CI/CD
  • AWS AWS
  • Azure Azure
  • GCP GCP
  • Kubernetes Kubernetes
  • Airflow Airflow
  • Apache Spark
  • PostGIS
  • ETL
  • ELT
  • Debezium
  • Data Lineage
  • Data Catalog
  • GDAL
  • GeoPandas
  • GeoServer
  • Infrastructure as Code
  • OGR
  • QGIS
  • Rasterio
  • ArcGIS
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.
ImageSat International