Python Solution Architect

Python Solution Architect (10+ Years)

Location: Trivandrum/Cochin

We are seeking an experienced Python Solution Architect to join our dynamic team. In this role, you will be responsible for designing and implementing scalable, high-performance software solutions that meet business requirements. You will collaborate with cross-functional teams to define architecture, best practices, and oversee the development process.

Job Responsibilities

•       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