Sr. Python Engineer - Microservices & Data Platforms

Overview

1. Python Microservices & API Development

• Design, develop, and maintain secure, scalable, and resilient microservices architectures using Python .
• Build and serve high-performance RESTful APIs utilizing asynchronous web frameworks such as FastAPI and Flask (or Django/Pyramid).
• Optimize concurrent connections and I/O operations using advanced asynchronous programming patterns ( asyncio ).
• Collaborate closely with front-end developers and cross-functional teams to integrate user-facing elements with complex server-side data logic.

2. Data Transformations & Schema Management

• Design, build, and optimize robust data transformation pipelines and ETL (Extract, Transform, Load) processes to clean, aggregate, and enrich large datasets for analytical consumption.
• Architect and maintain database schemas across both Relational and NoSQL data storage solutions, ensuring data integrity, quality, and consistency.
• Implement optimized data access layers using Object-Relational Mappers (ORMs) like SQLAlchemy or Django ORM to abstract and streamline CRUD operations, data queries, and transaction handling.

3. Security, DevOps & Platform Engineering

• Enforce security best practices across all microservices, implementing robust authentication, authorization, and encryption protocols using OAuth, JWT , and API Gateways .
• Act as a core developer focused on productionizing frameworks, taking ownership of developing and maintaining automated CI/CD pipelines .
• Utilize advanced debugging, logging, profiling, and testing techniques (unit testing, integration testing) to ensure code reliability.

Core Technical Stack (Essential)

• Programming & Frameworks: Expert Python development. Hands-on experience with FastAPI, Flask, asyncio , and routing/templating workflows.
• ORMs & Databases: Strong database manipulation using SQLAlchemy or Django ORM . High proficiency in writing complex SQL and database tuning.
• Security: Solid experience securing microservices via JWT, OAuth , and gateway configurations.
• Tooling & Scripting: Strong Shell scripting prowess and version control mastery ( Git workflow: branching, merging, pull requests).
• Engineering Practices: Demonstrated background productionizing code and configuring CI/CD automation.

Data Ecosystem Awareness & Preferred Skills

• Big Data Awareness: Familiarity with data warehousing concepts and Big Data technologies (e.g., Hadoop, Spark, Kafka ).
• Cloud & Containers (Preferred): Practical exposure to cloud platforms ( AWS, Azure, or GCP ) and containerization ( Docker, Kubernetes ).
• Data Governance (Preferred): Awareness of data compliance, data governance, and enterprise data security principles.

Qualifications & Experience

• Education: Bachelor s degree in Computer Science, Information Technology, or a related quantitative technical field.
• Experience: Proven track record as a Core Python/Data Engineer delivering production-grade microservices and data pipelines in an enterprise environment.
• Soft Skills: Exceptional problem-solving abilities with high attention to detail. Excellent communication, team collaboration, and documentation skills to present technical considerations effectively to stakeholders.