Python Solution Architect

Job Description - 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.