Architect scalable, efficient, and high-performance Python-based applications.
Design microservices architecture and cloud-native solutions using Python frameworks (e.g., Django, Flask, FastAPI).
Ensure Python solutions align with business goals and enterprise architecture.
Design and manage RESTful APIs and web services, leveraging Python's capabilities.
Expertise in selecting the right Python frameworks, libraries, and tools for different use cases.
Architect and optimize database interactions, including SQL and NoSQL databases.
Ensure efficient data processing, ETL pipelines, and integrations with data analytics platforms (e.g., Pandas, NumPy, SQLAlchemy).
Design seamless integrations with third-party services, APIs, and external systems using Python-based solutions.
Ensure smooth data flow between Python applications and other enterprise systems.
Architect solutions in cloud environments (AWS, GCP, Azure) using Python.
Implement CI/CD pipelines for Python projects and manage infrastructure-as-code (Terraform, Ansible).
Ensure security best practices in Python code (e.g., OWASP, cryptography, input validation).
Lead efforts to comply with data protection and regulatory requirements in Python solutions.
Provide guidance to Python developers on architectural decisions, design patterns, and code quality.
Mentor teams on Python best practices, writing clean, maintainable, and efficient code.
Work closely with customers, business analysts, project managers, and development teams to understand requirements.
Communicate complex technical concepts to non-technical stakeholders.

Ensure solutions address functional and non-functional requirements (e.g., performance, scalability, security).

Preferred Skills

Deep knowledge of Python frameworks like Django, Flask, or FastAPI.
Proficiency with asynchronous programming in Python (e.g., asyncio, concurrent.futures).
Hands-on experience with designing and deploying microservices-based architectures.
Understanding of containerization technologies like Docker and orchestration tools like Kubernetes.
Strong experience with AWS, GCP, or Azure for deploying and scaling Python applications.
Familiarity with cloud services like Lambda (AWS), Cloud Functions (GCP), or similar.
Experience with CI/CD pipelines and automation tools (e.g., Jenkins, GitLab CI, CircleCI).
Knowledge of Infrastructure-as-Code (IaC) tools like Terraform or Ansible.
Proficiency with relational databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Redis).
Experience with database optimization, indexing, and query tuning.
Strong understanding of RESTful APIs, GraphQL, and API documentation standards (e.g., OpenAPI/Swagger).
Experience with integrating third-party services via APIs.
Proficient with Git, GitHub, or GitLab for version control and collaboration in Python projects.
Familiarity with branching strategies (e.g., GitFlow) and code review practices.
Experience with Python security tools and practices (e.g., PyJWT, OAuth2, secure coding).
Familiarity with encryption, authentication, and data protection standards.
Hands-on experience working in Agile environments, familiar with Scrum or Kanban.
Ability to break down complex technical tasks into sprints and manage backlogs.
Knowledge of popular Python AI/ML libraries such as TensorFlow, PyTorch, and Scikit-learn.
Experience with deploying machine learning models in production environments.

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