Senior Python Developer

About the Role:

We are seeking a Senior Python Developer with deep expertise in SQL and relational databases to join our growing engineering team. In this role, you will design, develop, and maintain robust backend systems and data pipelines that power our core applications and analytics infrastructure.

This is a hands-on position requiring a strong technical foundation in Python programming and database architecture, along with the ability to work collaboratively across teams.

Responsibilities:

• Design, develop, and maintain scalable Python applications and backend services.
• Build and optimize complex SQL queries and stored procedures for data-intensive applications.
• Collaborate with product managers, data engineers, and DevOps to deliver end-to-end solutions.
• Write clean, efficient, and well-documented code with a focus on performance and reliability.
• Participate in code reviews, architectural discussions, and mentor junior developers.
• Troubleshoot and resolve software defects and performance issues in both application logic and SQL queries.
• Ensure security, scalability, and best practices in database design and application integration.
• Develop automated tests and ensure continuous integration and deployment pipelines are robust.
  

Requirements:

• 5+ years of professional experience in Python development.
• Strong proficiency in SQL, including performance tuning, indexing strategies, and working with large datasets.
• Solid understanding of relational databases (e.g., PostgreSQL, MySQL, SQL Server) and experience with database design and optimization.
• Familiarity with Python frameworks such as Django, Flask, or FastAPI.
• Experience integrating Python applications with databases and third-party APIs.
• Strong problem-solving and debugging skills.
• Knowledge of version control systems (e.g., Git).
• Familiarity with Docker, CI/CD tools, and cloud environments (e.g., AWS, Azure, GCP) is a plus.
  

Preferred Qualifications:

• Experience with ORMs (e.g., SQLAlchemy, Django ORM).
• Exposure to data engineering workflows or ETL pipelines.
• Familiarity with NoSQL databases and message queues (e.g., Redis, RabbitMQ, Kafka).
• Contributions to open-source projects or a public GitHub portfolio.