
Satellite Data Analyst Developer
3 days ago
Geospatial Software Engineer
The role involves developing software applications for geospatial data analysis and visualization using various tools and technologies.
Key Responsibilities
- Design, develop, and deploy a scalable pipeline to ingest and process satellite data from AWS, storing the results in an Amazon S3 data lake.
- Develop a framework to automate the machine learning lifecycle, including model training, validation, versioning, and storage of models for satellite image classification and thermal risk prediction.
- Design and build a low-latency REST API using AWS Lambda and API Gateway to serve real-time predictions from AI models.
- Implement the core features of an interactive dashboard using React and Mapbox GL JS, focusing on the intuitive visualisation of complex geospatial heatmap data.
- Design and construct the entire cloud infrastructure using Infrastructure as Code (IaC) principles with the AWS CDK, ensuring the platform is secure, cost-effective, and scalable.
Qualifications
Required Qualifications:
- A minimum of 3 years of professional software development experience.
- Deep expertise in either Python-based backend development or React-based frontend development.
- Essential, in-depth experience designing, building, and deploying services on Amazon Web Services (AWS), with a strong command of Lambda, S3, API Gateway, and IAM.
- A thorough understanding of REST principles and proven experience in designing and building APIs from scratch.
- Proficiency in containerising applications using Docker.
- Demonstrated ability to independently solve complex, open-ended technical challenges.
- Strong communication skills to articulate technical decisions and collaborate with the team.
Preferred Qualifications
- Experience building complex, interactive mapping and data visualisation services with Mapbox GL JS or similar libraries.
- Experience with GIS data processing using libraries like GeoPandas and Rasterio, or familiarity with Google Earth Engine.
- Experience with ML model serving (MLOps) using frameworks like XGBoost and Scikit-learn.
- Proven experience with Infrastructure as Code (IaC) tools such as AWS CDK or Terraform.
- Previous experience in an early-stage start-up, demonstrating the ability to build a product from version 0 to 1.
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