Python Developer with ETL and PostgreSQL
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About Us:
Radiant Digital delivers technology consulting and business solutions for commercial and government clients.
Our flexible delivery model allows us to provide end-to-end solution delivery, single project execution, and, or strategic resources.
CMMI Maturity Level III and ISO 9001 - 2015 certified.
Responsibilities:
We are seeking a skilled Python Developer with expertise in PostgreSQL database management, spatial data handling, and multiprocessing solutions. The ideal candidate will play a crucial role in designing, developing, and optimizing our spatial data processing pipelines and applications. Responsibilities :- Design, develop, and maintain Python-based applications and tools for spatial data analysis and visualization.
- Implement and optimize PostgreSQL database schemas, queries, and performance tuning for spatial data management.
- Develop multiprocessing solutions to enhance data processing efficiency and scalability.
- Collaborate with cross-functional teams to understand requirements and deliver robust, scalable solutions.
- Stay updated on industry trends and emerging technologies in spatial data analysis, Python development, and database management.
- Proven experience (8 years) in Python development, with a focus on data processing and analysis of spatial data.
- Strong proficiency in PostgreSQL database management, including schema design, query optimization, and performance tuning.
- Experience working with spatial data formats (e.g., GeoJSON, Shapefiles) and libraries (e.g., GeoPandas, Shapely).
- Familiarity with multiprocessing techniques and libraries (e.g., multiprocessing, concurrent.futures) for parallel processing.
- Excellent problem-solving skills and ability to work effectively in a fast-paced, collaborative environment.
- Strong communication skills and ability to articulate technical concepts to non-technical stakeholders.
- Master's degree in Computer Science, Engineering, or related field.
- Experience with GIS (Geographic Information Systems) tools and libraries (e.g., GDAL, PostGIS).
- Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and related services (e.g., S3, EC2, Google BigQuery).
- Familiarity with containerization technologies (e.g., Docker, Kubernetes) for deployment and scalability.
- Contributions to open-source projects related to Python development or spatial data analysis.
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