Python Developer

We are looking for a skilled Python Developer to join our Core Team and help build and scale our high-load Geospatial AI Data Platform. In this role, you will productionize Data Science models and convert massive volumes of raw imagery into structured, meaningful insights that power our client-facing products. If you enjoy solving complex, large-scale data challenges, this position is an excellent fit.

Key Responsibilities

Data Pipeline Development

• Build and optimize ETL pipelines for collecting, cleaning, transforming, and loading large geospatial datasets.

API Development

• Design, develop, and maintain high-performance, scalable RESTful APIs (FastAPI or AWS Lambda Powertools).

Model Serving

• Collaborate with Data Scientists to containerize, deploy, and maintain models within our Geospatial AI Platform.

Code Quality & Performance

• Write clean, efficient, and reusable Python code; optimize data processing speed and platform latency for large-scale workloads.

System Architecture

• Contribute to the design and evolution of Microservices and Serverless architectures, ensuring high availability, scalability, security, and observability.

Collaboration

• Work in an Agile environment with Data Scientists, DevOps, and Product Managers to translate business needs into technical solutions.

   

Requirements

• B.Sc. in Computer Science or a related field
• 4+ years of professional experience in Python backend development, especially with data-intensive systems
• Strong expertise in Python 3 and adherence to PEP8
• Solid OOP skills and understanding of SOLID principles
• Proven experience building production-ready APIs (FastAPI or Lambda Powertools)
• Hands-on experience with AWS services: S3, SQS, EC2, API Gateway, Lambda, DynamoDB, CloudFormation/SAM
• Experience with Docker/Kubernetes
• Strong Linux experience (preferably Ubuntu)
• Knowledge of SQL databases (PostgreSQL preferred)
• Proficiency with Git and collaborative workflows

• Good communication skills in English

   

Nice to Have

• Experience with geospatial libraries (GeoPandas, GDAL, Shapely, Rasterio)
• Familiarity with model serving platforms (e.g., NVIDIA Triton)
• Experience with workflow orchestration tools such as Apache Airflow
• Experience working with on-prem infrastructure
• Knowledge of CI/CD practices (GitHub Actions) and DevOps methodologies