Full Stack Python React Engineer

Company Description

About the Role

Tech Stack

• Backend: Python, Flask, SQLAlchemy, NumPy/Pandas/SciPy
• Frontend: React, Material-UI, TypeScript, Plotly/Recharts
• Database: MariaDB, with plans for PostgreSQL and Redis
• Infrastructure: Docker, Terraform, AWS (EC2, S3, ECR), Cloudflare
• Target Stack: Celery, Redis, FastAPI, Kubernetes/ECS
  

Key Responsibilities

Architecture & Scaling (40%)

• Lead migration from synchronous Flask to async processing with Celery/Redis
• Design and implement horizontal scaling strategy with load balancing
• Architect transition from file-based to distributed state management
• Implement proper caching layers and database replication
• Establish WebSocket connections for real-time analysis updates
  

Development & Features (30%)

• Build integrated analytics database system for biopharma benchmarking data
• Develop RESTful and GraphQL APIs for complex data operations
• Implement advanced Monte Carlo simulation optimizations
• Create real-time collaborative features for portfolio planning
• Enhance React frontend with better state management
  

Quality & Testing (20%)

• Establish comprehensive testing framework (pytest, Jest, React Testing Library)
• Implement CI/CD pipelines with automated testing and deployment
• Set up monitoring and observability
• Conduct code reviews and establish coding standards
  

Mentorship & Leadership (10%)

• Mentor junior engineers on best practices and architecture patterns
• Lead technical design discussions and document architectural decisions
• Collaborate with stakeholders to translate business needs into technical solutions
  

Qualifications

Required Qualifications

• 5+ years of fullstack development experience
• Strong Python backend development (Flask/FastAPI)
• Production React experience with modern patterns (hooks, context, TypeScript)
• Experience scaling applications from monolith to microservices
• Proficiency with SQL databases and query optimization
• Experience with Docker, cloud deployment (AWS preferred), and IaC tools
• Strong understanding of async programming and distributed systems
• Experience with data-intensive applications and scientific computing
  

Preferred Qualifications

• Experience in pharmaceutical, biotech, or financial analytics domains
• Knowledge of statistical modeling and Monte Carlo methods
• Experience with Terraform and Kubernetes
• Familiarity with data visualization libraries (Plotly, ReCharts)
• Experience implementing RAG systems or LLM integrations
• Background in building multi-tenant SaaS platforms
  

What You'll Achieve

• Year 1: Lead architecture modernization, implement testing framework, deploy horizontal scaling
• Year 2: Launch integrated analytics database, achieve 10x performance improvement
• Build a platform handling 100+ concurrent users and million-point simulations
  

• Dental care
• Life insurance