Job
Description
We are seeking an experienced Architect to drive the development of high-performance Data Processing applications. The ideal candidate will be a hands-on technical leader with previous experience as either a Technical Lead or Technical Architect, bringing deep expertise in Python, AI/ML. This role combines technical leadership with hands-on development, ensuring best coding practices, Agile methodologies, and efficient software delivery to create scalable data solutions. Key Responsibilities Develop and enhance Data Processing applications using Python and Django Framework Build, train, test, and optimize ML models using industry best practices Establish and enforce code quality standards, security protocols, and performance optimization Lead and collaborate with cross-functional teams to define, design, and deploy new features Maintain and improve Agile workflows, including JIRA board tracking Coordinate and participate in code reviews, troubleshooting, and debugging activities Research and implement emerging Python libraries, tools, and best practices Provide technical guidance and mentorship to development teams Communicate effectively with stakeholders and project teams on technical matters Architect scalable solutions that align with business requirements and technical constraints Required Skills & Qualifications Previous experience as a Technical Lead or Technical Architect Proven experience in designing scalable Python-based Data Processing & Analytics architectures Expertise in Microservice and Event-driven architectures Extensive development experience in Python with strong problem-solving capabilities Minimum 2+ years of experience with Django Framework Advanced knowledge of Object-Oriented Programming concepts Hands-on experience with PostgreSQL/MySQL database systems Demonstrated experience integrating db_connectors package with diverse data stores (PostgreSQL, MySQL, Redis, CSV, BigQuery, etc.) Practical experience with Airflow Process Orchestration Proficiency in data science libraries including Scikit-learn, Pandas, and NumPy Experience implementing and managing Celery Beat schedulers Knowledge of streaming technologies, caching solutions (Redis, Memcached), and message brokering systems (ActiveMQ) Demonstrated experience with Agile methodologies and JIRA Proficiency with version control systems (Git/GitHub/GitLab) Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders Nice to Have Knowledge of Jenkins CI/CD pipelines, Docker, and Cloud deployment strategies Exposure to DevOps practices and Server Management Experience with data visualization tools and techniques Background in performance optimization for large-scale data systems Experience mentoring junior developers
