• We’re looking for a skilled and motivated Data Engineer to build and maintain robust, scalable data infrastructure for geospatial and time-series datasets.
•  You’ll design efficient databases, develop ETL/ELT pipelines, and ensure high-performance data access for multiple users and applications.
• Build and maintain scalable ETL/ELT pipelines for geospatial and time-series data.
• Design and optimize databases (PostgreSQL/PostGIS, TimescaleDB, InfluxDB, or NoSQL) for efficient storage and querying.
• Identify and fix performance bottlenecks to support real-time analytical workloads.
• Develop effective data models ensuring quality, integrity, and accessibility.
• Monitor and maintain the data platform for stability, security, and scalability.
• Collaborate with data scientists, analysts, and engineers to deliver reliable solutions.

 If you’re interested, please send your CV to the e-mail address in the Apply for job button.

• 2+ years of experience as a Data Engineer in large-scale production environments.
• Strong geospatial data knowledge (PostGIS, GeoServer, projections, spatial indexing).
• Experience managing time-series data (InfluxDB, TimescaleDB, etc.).
• Proficiency in Python for scripting and data pipeline orchestration.
• Advanced SQL and database design/optimization skills.
• Experience with cloud platforms (AWS, Azure, GCP) and orchestration tools (Airflow, Prefect, Dagster).
• Ability to design scalable systems handling large, fast-moving data.

 Desirable Skills

• Experience with streaming technologies (Kafka, Kinesis).
• Knowledge of geospatial formats (GeoJSON, Shapefile, Parquet).
• Familiarity with Docker or Kubernetes.
• Experience with data warehouses (Snowflake, BigQuery, Redshift).