59 минут назад
Data Engineer (Geospatial)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer (Geospatial) (Python/AWS): Building and hardening the delivery and serving backbone for satellite-based infrastructure monitoring with an accent on backend services, geospatial data processing, and workflow orchestration. Focus on designing deterministic Prefect and AWS pipelines, automating data-quality checks, managing PostGIS schemas, and keeping customer-ready insights traceable and reliable at scale.
Location: GmbH Berlin Office, hybrid
Company
develops satellite analytics products that monitor changes around critical infrastructure such as pipelines and power grids.
What you will do
- Co-own and extend delivery-management, insight-generation, and post-processing services that turn model detections into customer-ready insights.
- Harden backend services with testing, documentation, and reliable ownership practices.
- Maintain the AWS and Prefect delivery platform, including Lambda-based integrations, orchestration flows, and cross-repository releases.
- Manage PostgreSQL and PostGIS schemas and Alembic migrations.
- Unblock orchestration runs, reduce manual delivery steps, and maintain delivery SLAs.
- Automate schema, geometry, and coverage-quality checks while maintaining traceable metadata and STAC entries.
Requirements
- Strong production experience with Python.
- Experience building and operating backend services with FastAPI or similar frameworks, SQLAlchemy, Alembic, and Pydantic.
- Production experience with AWS, especially S3, Lambda, EC2, and IAM basics.
- Experience with PostgreSQL, spatial data, and orchestration tools such as Prefect, Airflow, or Dagster.
- Ability to handle geospatial raster and vector data using tools such as Rasterio, GeoPandas, Shapely, STAC, and Cloud-Optimised GeoTIFF.
- Pragmatic delivery, reliability, operations, ownership, and verification mindset.
Nice to have
- Experience with PostGIS, GeoAlchemy2, Ray, or Anyscale.
- Experience with MLflow, experiment and dataset versioning, or remote sensing and SAR data.
- Knowledge of observability tools such as structured logging, OpenTelemetry, and alerting.
- Experience with satellite provider APIs including Capella, UP42, Planet, or ICEYE.
Culture & Benefits
- Flexible working hours and a hybrid work model.
- Career development support, autonomy, and opportunities for creative initiative.
- Overtime is limited to necessary situations and offset with time off and rest.
- Internal workshops, knowledge-sharing sessions, journal clubs, and hackathons.
- Central Berlin Kreuzberg office with free fruit, nuts, and drinks.
- Potential employee stock option participation, Urban Sports membership, BVG subsidy, and a corporate pension program.
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