Senior Python Developer- Bench Marking

Company: Indian / Global Digital Organization

Key Skills: Fullstack Python, Python, Data Engineer, Data Science, Data Scientist, Data Engineering

Roles and Responsibilities:

• System Architecture & Development: Architect, develop, and optimize Python-based applications, frameworks, and libraries to support large-scale benchmarking and high performance data processing.
• End-to-End Ownership: Drive the entire project lifecycle--from design and implementation to deployment, testing, and ongoing maintenance.
• Active Data Science & Engineering Involvement: Contribute to data science modeling and data pipeline creation (ETL, Big Data, etc.), ensuring optimal integration and top-notch performance.
• AI Tools & Automation: Leverage AI-driven developer tools and automation frameworks to streamline coding, testing, and deployment, enabling faster iteration and enhanced productivity.
• Benchmarking Solutions: Build cutting-edge benchmarking tools, develop performance metrics, and set up test frameworks to measure system efficiency and reliability.
• Best Practices & Code Quality: Champion coding standards, code reviews, and automated testing to maintain high-quality, maintainable code.
• Documentation & Reporting: Produce clear, concise documentation for both technical and non-technical stakeholders, detailing system architecture, benchmark results, and best practices.

Skills Required:

• Experience: Minimum of 8 years of professional experience in Python development, emphasizing large-scale, production-ready systems.
• Technical Expertise:
• Advanced Python skills, including a deep understanding of its libraries (e.g., NumPy, Pandas, Flask/FastAPI).
• Strong software design and architecture know-how (microservices, serverless, etc.).
• Proficiency in performance tuning, algorithms, data structures, and CI/CD pipelines.
• Data Science & Engineering Exposure:
• Hands-on experience or solid familiarity with data engineering workflows, big data ecosystems (e.g., Spark, Hadoop), and data warehousing.
• Understanding of data science tools and frameworks (e.g., Jupyter, scikit-learn, PyTorch) and their practical implementation.
• Teamwork & Communication: Demonstrated ability to communicate complex technical ideas, adapt in a fast-paced setting, and drive collaborative success.

Preferred Skills

• Experience with containerization (Docker, Kubernetes) and cloud platforms (AWS, Azure, GCP).
• Familiarity with Agile or Scrum processes.
• Background in DevOps tools and pipelines.

Education: Bachelor's degree or higher in computer science, Software Engineering, or related field. Equivalent work experience is also welcomed