Job Responsibilities:

Design, develop, maintain, and optimize Python-based applications and data-oriented solutions.
Apply modern software engineering principles, including:
Object-Oriented Programming (OOP)
Modular and reusable code design
Unit and automated testing
Git-based version control
Software Development Lifecycle (SDLC) practices
Code review and documentation
Performance and code optimization
Analyze existing and legacy Python code and refactor or redesign it according to modern software engineering standards.
Improve code quality, maintainability, testability, performance, and reliability.
Work with relational databases and develop efficient SQL queries for data extraction, transformation, and analysis.
Understand and work with common data structures, data models, transformations, and data processing concepts.
Contribute to the development and optimization of data pipelines and data-processing workflows.
Collaborate with data engineers, data scientists, analysts, and other technical stakeholders.
Support the transition of analytical or prototype solutions into robust, production-ready implementations.
Identify technical bottlenecks and propose practical improvements to existing solutions.
Where applicable, contribute to solutions involving Databricks, Data Science, Machine Learning, and AI.

Job Requirements:

The following knowledge, skills, and abilities acquired through a combination of formal schooling, self-education, prior experience, or on-the-job training.

Design, develop, maintain, and optimize Python-based applications and data-oriented solutions.
Apply modern software engineering principles, including:
Object-Oriented Programming (OOP)
Modular and reusable code design
Unit and automated testing
Git-based version control
Software Development Lifecycle (SDLC) practices
Code review and documentation
Performance and code optimization
Analyze existing and legacy Python code and refactor or redesign it according to modern software engineering standards.
Improve code quality, maintainability, testability, performance, and reliability.
Work with relational databases and develop efficient SQL queries for data extraction, transformation, and analysis.
Understand and work with common data structures, data models, transformations, and data processing concepts.
Contribute to the development and optimization of data pipelines and data-processing workflows.
Collaborate with data engineers, data scientists, analysts, and other technical stakeholders.
Support the transition of analytical or prototype solutions into robust, production-ready implementations.
Identify technical bottlenecks and propose practical improvements to existing solutions.
Where applicable, contribute to solutions involving Databricks, Data Science, Machine Learning, and AI.

The following knowledge, skills, and abilities acquired through a combination of formal schooling, self-education, prior experience, or on-the-job training.

Design, develop, maintain, and optimize Python-based applications and data-oriented solutions.
Apply modern software engineering principles, including:
Object-Oriented Programming (OOP)
Modular and reusable code design
Unit and automated testing
Git-based version control
Software Development Lifecycle (SDLC) practices
Code review and documentation
Performance and code optimization
Analyze existing and legacy Python code and refactor or redesign it according to modern software engineering standards.
Improve code quality, maintainability, testability, performance, and reliability.
Work with relational databases and develop efficient SQL queries for data extraction, transformation, and analysis.
Understand and work with common data structures, data models, transformations, and data processing concepts.
Contribute to the development and optimization of data pipelines and data-processing workflows.
Collaborate with data engineers, data scientists, analysts, and other technical stakeholders.
Support the transition of analytical or prototype solutions into robust, production-ready implementations.
Identify technical bottlenecks and propose practical improvements to existing solutions.
Where applicable, contribute to solutions involving Databricks, Data Science, Machine Learning, and AI.

The following knowledge, skills, and abilities acquired through a combination of formal schooling, self-education, prior experience, or on-the-job training.