Python Backend

• Design, develop, and implement scalable backend systems using Python, with a focus on microservices and API-driven architecture.
• Build and maintain RESTful APIs and backend services for data ingestion, processing, and integration.
• Develop data processing pipelines to handle structured and unstructured data.
• Collaborate with global Technology teams across multiple time zones in a hybrid environment.
• Apply Object-Oriented Programming (OOP) principles and backend engineering best practices.
• Drive resolution of complex technical challenges through analysis of system flows and business processes.
• Ensure solutions align with enterprise architecture, performance, and scalability requirements.
• Establish and follow standards for coding, testing, debugging, and deployment in backend environments.
• Perform data extraction, transformation, and analysis to support business use cases.
• Implement unit testing and TDD to ensure reliability and maintainability of backend services.
• Contribute to microservices ecosystem, including service integration and inter-service communication.
• Support the integration of LLMs and GenAI capabilities into backend systems and workflows.
• Mentor junior developers and promote strong engineering and coding standards.
• Identify and manage risks, ensuring compliance with policies, regulatory requirements, and governance standards.

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field.
• Minimum 5 years of experience developing backend systems and services using Python.
• Strong proficiency in Python and related libraries (e.g., NumPy, Pandas).
• Experience building REST APIs and working in microservices or service-oriented architectures.
• Experience with data processing, ETL pipelines, or data engineering concepts.
• Familiarity with LLMs and GenAI technologies.
• Understanding of distributed systems and backend integration patterns.
• Ability to work independently and collaboratively in a global team.

Preferred Skills:

• Experience with distributed data tools (e.g., Hadoop, Spark, Hive).
• Knowledge of databases (e.g., MySQL or other relational databases).
• Familiarity with containerization (Docker) and orchestration (Kubernetes/OpenShift).
• Background in financial services, banking, or risk environments.
• Experience with AI developer tools such as Copilot.