About the Role We are seeking a highly skilled Senior Python Data Engineer with strong experience in building and maintaining production-grade data pipelines, developing scalable backend services, and working with large-scale distributed data systems. The ideal candidate should possess a strong engineering mindset and be capable of transforming analytical workflows into robust, maintainable, and production-ready applications.
Key Responsibilities Design, develop, and maintain scalable Python-based data pipelines for data ingestion,transformation, processing, and publishing across distributed systems. Convert notebook-based analyses and Databricks workflows into modular, reusable, testable,and production-ready Python applications. Build and maintain backend APIs and services using Python frameworks such as Flask.Design efficient data models and retrieval mechanisms using SQL and NoSQL databases, with apreference for MongoDB.
Collaborate closely with Data Scientists to operationalize research models and analyticalworkflows. Develop reusable data access layers, shared services, and engineering frameworks to improvedevelopment efficiency. Work with geospatial datasets and implement location-based data processing solutions.Ensure code quality through best practices, testing, documentation, and performanceoptimization. 1 Participate in architecture discussions and contribute to technical decision-making.
Required Skills &
Qualifications Python &
Key Responsibilities Design, develop, and maintain scalable Python-based data pipelines for data ingestion,transformation, processing, and publishing across distributed systems. Convert notebook-based analyses and Databricks workflows into modular, reusable, testable,and production-ready Python applications. Build and maintain backend APIs and services using Python frameworks such as Flask.Design efficient data models and retrieval mechanisms using SQL and NoSQL databases, with apreference for MongoDB.
Collaborate closely with Data Scientists to operationalize research models and analyticalworkflows. Develop reusable data access layers, shared services, and engineering frameworks to improvedevelopment efficiency. Work with geospatial datasets and implement location-based data processing solutions.Ensure code quality through best practices, testing, documentation, and performanceoptimization. 1 Participate in architecture discussions and contribute to technical decision-making.
Required Skills &
Qualifications Python &
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