<p>Job Description :</p><p><br/></p><p>Key Responsibilities :</p><p><br/></p><p>- Lead the design, development, and deployment of Python-based applications and services.
</p><p><br/></p><p>- Define technical architecture, ensure code quality, performance, and scalability of applications.
</p><p><br/></p><p>- Develop RESTful APIs and microservices using frameworks like Flask, Django, or FastAPI.
</p><p><br/></p><p>- Drive adoption of best coding practices, automated testing, and CI/CD principles across the team.
</p><p><br/></p><p>- Conduct code reviews, provide technical mentorship, and foster an environment of learning and innovation.
</p><p><br/></p><p>- Work extensively with Apache Spark, PySpark, and related big data technologies for data transformation and analytics.
</p><p><br/></p><p>- Manage and maintain database systems (SQL, PostgreSQL, MongoDB, etc.) ensuring data integrity and performance.
</p><p><br/></p><p>- Implement serverless solutions, containerization (Docker, Kubernetes), and infrastructure automation where applicable.
</p><p><br/></p><p>- Ensure security, scalability, and high availability of cloud-based services.
</p><p><br/></p><p>- Work closely with Product Managers, Data Scientists, and DevOps teams to deliver end-to-end solutions.
</p><p><br/></p><p>- Translate business requirements into technical specifications and actionable tasks.
</p><p><br/></p><p>- Manage project timelines, sprint planning, and release cycles to ensure on-time delivery.
</p><p><br/></p><p>Mandatory Skills & Experience :</p><p><br/></p><p>- 4-6 years of experience in software engineering with a strong focus on Python-based solutions.
</p><p><br/></p><p>- Proven experience with Python frameworks (Flask, Django, FastAPI).
</p><p><br/></p><p>- Strong knowledge of SQL and database technologies (PostgreSQL, MySQL, MongoDB).
</p><p><br/></p><p>- Solid understanding of cloud platforms (AWS, Azure, or GCP) with hands-on deployment experience.</p><p><br/></p><p>- Familiarity with container orchestration tools (Docker, Kubernetes).
</p><p><br/></p><p>- Excellent analytical, debugging, and problem-solving abilities.
</p><p><br/></p><p>Preferred Skills :</p><p><br/></p><p>- Exposure to data science and analytics tools such as R, Pandas, NumPy, Scikit-learn.
</p><p><br/></p><p>- Experience with data lakes, warehouses, or streaming platforms (Kafka, Kinesis).</p><p><br/></p><p>- Familiarity with machine learning model integration within production-grade systems.</p> (ref:hirist.tech)