Geospatial Cloud Engineer (AWS)

【Responsibilities】

»Design, build, and operate scalable AWS pipelines for satellite imagery and large geospatial datasets.

»Architect and optimize cloud infrastructure for batch and asynchronous geospatial processing, with a focus on performance, reliability, scalability, and cost.

»Productionize AI/ML and remote-sensing algorithms into reliable, automated processing workflows.

»Build and maintain pipelines using AWS services such as S3, AWS Batch, ECS/EKS, Step Functions, Lambda, EventBridge, and CloudWatch.

»Design efficient parallel-processing strategies for large imagery datasets, including job orchestration, retries, failure recovery, monitoring, and intermediate data management.

»Implement Infrastructure as Code, automated deployments, and production-grade monitoring, logging, alerting, and operational dashboards.

»Collaborate with Data Scientists, Software Engineers, and Data Engineering teams to integrate processing workflows with user-facing applications, APIs, and the broader geospatial data platform.

»Evaluate new AWS services and cloud-processing architectures as workload and platform requirements evolve.

【Required Skills & Experience】

»3+ years of experience in Cloud Engineering, Platform Engineering, Data Engineering, DevOps/SRE, or a related field.

»Strong production experience with AWS and Python.

»Strong experience with Docker and containerized workloads.

»Experience with Infrastructure as Code (Terraform, CloudFormation, or CDK).

»Experience designing distributed or large-scale data-processing systems.

»Familiarity with geospatial technologies such as GeoTIFF, COG, STAC, GDAL, Rasterio, GeoPandas, Xarray, or PostGIS

【Preferred Skills & Experience】

»Expertise in processing satellite imagery or remote-sensing data at scale.

»Experience with spatial tiling, mosaicking, reprojection, masking, or AOI-based processing.

»Familiarity with AWS Spot Instances, Savings Plans, S3 lifecycle policies, or FinOps practices.

»Experience with Kubernetes or distributed computing frameworks such as Dask, Ray, or Spark.

»Ability to use SQS, Kafka, Kinesis, or similar messaging/streaming systems.

»Experience with GPU-based or compute-intensive workloads.

»Familiarity with ML/MLOps workflows.

【What We’re Looking For】

»Experience working with geospatial or satellite data

»Familiarity with Docker, Kubernetes, Terraform, and CI/CD

»Experience with databases such as PostgreSQL/PostGIS

»Ability to work across technical domains and independently solve complex problems

»Comfortable collaborating in a fast-paced, globally distributed team

【Work Location】

Remote / Japan preferred but not limited to.

This role is remote-friendly within the APAC region, with candidates based in Japan especially welcome.

【Work Style】

09:00 ～ 18:00 （Break： 12:00 ～ 13:00 ）JST

Flexible Working Hours System

»Workdays: 5 days per week (Monday - Friday)

»Acceptable Working Hours: 5:00 AM – 10:00 PM (including a 60-minute break)