Technical Manager/Solution Architect
2 months ago
Key Responsibilities :
- Team Leadership : Manage and mentor a team of engineers, providing guidance on best practices, conducting code reviews, and supporting career development.
- Hands-on Development : Lead the development of high-quality Python-based applications, providing hands-on coding when necessary.
- Project Delivery : Oversee the planning, execution, and delivery of technical projects, ensuring that timelines, scope, and quality targets are met.
- System Architecture Design : Define and design scalable, resilient, and secure architectures for new and existing systems using Python and other relevant technologies.
- Technical Strategy : Collaborate with stakeholders to develop the technical strategy and roadmap, ensuring alignment with business goals.
- Cross-functional Collaboration : Work closely with product managers, DevOps, and data science teams to ensure seamless integration and functionality.
- Technology Evaluation : Evaluate emerging technologies and frameworks to ensure that the architecture remains current and effective for future scalability and innovation.
- Proof of Concepts : Develop and prototype architectural solutions, ensuring feasibility and scalability before full implementation.
- Quality Assurance : Establish and enforce best practices for coding, testing, continuous integration (CI/CD), and documentation to ensure code quality and maintainability.
- DevOps Integration : Guide the team in implementing and maintaining robust CI/CD pipelines, automated testing, and monitoring.
- Performance Optimization : Ensure the system's performance and reliability through profiling, optimization, and scaling strategies.
- Requirement Gathering : Collaborate with product owners and business stakeholders to gather and analyze functional and non-functional requirements.
- Technical Communication : Act as the primary technical contact, explaining complex technical concepts to non-technical stakeholders and ensuring clear communication across teams.
- Risk Management : Identify technical risks in the architecture or system and develop mitigation strategies to prevent or resolve them.
- Innovation : Drive innovation within the team by encouraging experimentation and the adoption of modern development practices and tools.
- Team Development : Foster a culture of continuous learning and improvement, supporting team members in expanding their technical expertise.
- Mentorship : Provide guidance on both development and architecture, ensuring that the team adheres to high technical standards.
Required Skills and Qualifications :
- Educational Background : Bachelor's or Master's degree in Computer Science, Engineering, or related field.
- Experience : Minimum of 7-10 years of experience in software development, with at least 3 years in a managerial or technical leadership role, and 2+ years of solution architecture experience.
Technical Expertise :
- Expertise in Python and Python frameworks (e.g, Django, Flask, FastAPI) with a deep understanding of object-oriented programming, design patterns, and best practices.
- System Design : Strong knowledge of system design, architecture patterns (e.g, microservices, event-driven), and cloud infrastructure (AWS, GCP, Azure).
- Experience with databases (both relational and NoSQL), distributed systems, and large-scale web applications.
- Strong familiarity with DevOps practices, CI/CD pipelines, containerization (Docker, Kubernetes), and cloud deployment strategies.
- API Design and Integration : Extensive experience in RESTful API and microservices architecture.
- Leadership Skills : Proven experience managing and mentoring teams, driving technical excellence and delivering on complex projects.
- Analytical Problem Solving : Strong analytical skills for troubleshooting and solving complex technical problems.
- Communication : Excellent verbal and written communication skills, with the ability to articulate technical information to diverse audiences.
Preferred Qualifications :
- Extensive knowledge of Python Frameworks
- Experience in Agile or Scrum environments.
- Knowledge of data science libraries (e.g, Pandas, Numpy) and machine learning frameworks (e.g, TensorFlow, PyTorch) is a plus
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