Python Developer
Confirmed on the employer's own hiring board on Sep 26, 2026. First seen by Alion on Dec 30, 2025.
Employment Type: Full-Time, Permanent Overview: We are seeking an experienced Senior Python Developer with experience in Streamlit, database development, and a strong understanding of Power BI. If you are passionate about data visualization, Python development, and crafting scalable solutions, we’d love to hear from you.
Key
Responsibilities Application Development Develop sophisticated Streamlit applications and dashboards to deliver actionable insights. Implement back-end functionalities with a focus on seamless integration between web applications and databases. Database Development Be familiar with database operations and development (SingleStore, Snowflake, SQL Server, MongoDB, etc.). Code Quality & Best Practices Write high-quality, reusable, and maintainable code in Python. Conduct code reviews and ensure adherence to software development best practices. Deployment & Monitoring Manage application deployment and performance monitoring on cloud platforms (AWS, GCP, Azure, etc.). Address bugs and performance bottlenecks in a timely manner, ensuring high application uptime.
Qualifications Experience Minimum 5+ years of professional experience in Python development. Strong track record of building web applications with Streamlit and integrating real-time databases. Hands-on experience defining insights and creating visualizations in Power BI. Proven expertise in working with relational (e.g., SQL, PostgreSQL) and non-relational (e.g., MongoDB) databases.
Technical Skills Strong understanding of Python frameworks and libraries for data processing. Proficiency with database design, optimization, and analytics. Familiarity with cloud environments and DevOps practices for application deployment.
Soft Skills Strong problem-solving, analytical, and debugging skills. Excellent communication skills - ability to articulate concepts and solutions clearly. Good to Have (GenAI / AI Skills): Experience integrating Generative AI capabilities into applications using APIs (e.g., OpenAI, Azure OpenAI, AWS Bedrock, or similar). Familiarity with building AI-powered features such as natural language querying, conversational interfaces, or intelligent assistants on top of data applications. Basic understanding of Retrieval-Augmented Generation (RAG) concepts and vector databases (e.g., ChromaDB, Pinecone, FAISS, or similar). Experience using Python libraries for AI/LLM integration (LangChain, LlamaIndex, or equivalent frameworks). Understanding of prompt engineering and techniques to improve response quality, reliability, and relevance. Awareness of data privacy, security, and responsible AI considerations when working with GenAI-enabled systems.