Python Developer

We are seeking a highly skilled and motivated Python Developer to join our Core Team and help build and scale a high-load Geospatial AI Data Platform. In this role, you will be responsible for productionizing Data Science models and transforming massive volumes of raw aerial imagery into structured, actionable insights that power our client-facing products. You will work closely with Data Scientists, DevOps, and Product teams to deliver reliable, scalable, and high-performance solutions in a cloud-native environment.

Key Responsibilities:

• Data Pipeline Development:
  Design, build, and optimize ETL pipelines for ingesting, cleaning, transforming, and processing large-scale geospatial datasets and aerial imagery.
• API Development:
  Design, develop, and maintain high-performance, scalable RESTful APIs using FastAPI or AWS Lambda Powertools.
• Model Serving & Productionization:
  Collaborate with Data Scientists to containerize, deploy, and maintain machine learning models in production environments.
• Code Quality & Performance Optimization:
  Write clean, efficient, and reusable Python code; optimize data processing throughput and platform latency for large-scale workloads.
• System Architecture:
  Contribute to the design and evolution of Microservices and Serverless architectures, ensuring scalability, security, availability, and observability.
• Cross-functional Collaboration:
  Work in an Agile environment with Data Scientists, DevOps Engineers, and Product Managers to translate business requirements into robust technical solutions.

Required Qualifications:

1. Python & Backend Development

• Python Expertise:
  4+ years of professional experience in Python backend development, particularly in data-intensive or high-load systems.
• Code Quality:
  Strong knowledge of Python 3, adherence to PEP8 standards, solid OOP skills, and understanding of SOLID principles.
• API Development:
  Proven experience building and maintaining production-ready APIs using FastAPI or AWS Lambda Powertools.

2. Cloud & Infrastructure

• AWS Experience:
  Hands-on experience with AWS services including S3, SQS, EC2, API Gateway, Lambda, DynamoDB, CloudFormation / SAM.
• Containers:
  Experience working with Docker and Kubernetes in production environments.
• Linux:
  Strong Linux administration experience (Ubuntu preferred).

3. Databases & Data Storage

• Relational Databases:
  Solid experience working with SQL databases, preferably PostgreSQL.
• Data Handling:
  Experience designing systems that process large datasets efficiently and reliably.

4. Engineering Practices

• Version Control:
  Proficiency with Git and collaborative development workflows.

• Communication:
  Good English communication skills and ability to work effectively in a distributed, cross-functional team.

   

Preferred / Bonus Qualifications:

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