Role Overview: Data Analysis and Engineering Expert for Geospatial Navigation App
Introduction
In my role, I focused on data analysis and the development of Python modules for a vehicle navigation app. My expertise lies in handling and interpreting geospatial data, derived from a variety of sources, and in deploying robust solutions on AWS using Docker.
Technologies and Expertise
- Python: The core language for all development, used for scripting and building Python modules.
- Pandas & Numpy: Essential for data manipulation and numerical analysis in Python.
- SNS Plots & Pyplot: Utilized for data visualization, crucial in understanding and presenting data trends.
- Shapely: Employed for geometric and spatial analysis within our geospatial data tasks.
- AWS & Docker: Responsible for deployment and monitoring, ensuring scalable and efficient application performance.
- AWS Services (SQS, S3, EC2): Key components in managing the application's infrastructure, data storage, and scalability.
Role in Action
- Engineering New Features: I developed new features for the Python modules, enhancing the app's functionality.
- Geospatial Data Analysis: Specialized in analyzing geospatial data from external (e.g., car navigation systems) and internal sources (HERE navigation), determining the best data sources.
- Optimization of Navigation: Aimed to identify optimal maneuvers for vehicles in each tile, improving navigation accuracy.
- Deployment and Monitoring: Managed the application's deployment on AWS, using Docker for containerization and a pipeline for smooth operation.
- Team Collaboration: As part of a Chicago-based team, I communicated effectively in English, ensuring seamless teamwork and knowledge sharing.