Senior Python Developer / Architect

Architected and implemented microservices-driven backend systems using Python, Django, Flask, and FastAPI for enterprise-scale applications. Designed RESTful and SOAP APIs for secure, scalable, and high-performance backend services, integrating with front-end clients (AngularJS/Vue.js/React). Developed real-time data pipelines using Kafka, Spark Streaming, and Celery, processing millions of records per day. Built serverless applications using AWS Lambda, API Gateway, and DynamoDB, reducing operational overhead by 40%. Designed and maintained multi-cloud infrastructure using Terraform, CloudFormation, and Ansible for AWS, Azure, and GCP. Led the design and deployment of containerized applications with Docker and Kubernetes (EKS), improving scalability and uptime. Implemented authentication and authorization using OAuth, SAML, AWS Cognito, and LDAP integrations. Designed and implemented CI/CD pipelines using Jenkins, GitHub Actions, ArgoCD, and SonarQube for automated testing, code quality, and deployments. Developed AI/ML pipelines for predictive analytics, NLP, and deep learning models using TensorFlow, PyTorch, Keras, and Spark MLlib. Built and maintained NoSQL and SQL databases, designing schemas for PostgreSQL, MySQL, MongoDB, and Cassandra for high availability. Conducted performance tuning and optimization for Python backend services, reducing API response times by up to 35%. Developed automated data ingestion and ETL pipelines using Python, Pandas, NumPy, and Spark. Implemented monitoring and observability using ELK Stack, Prometheus, Grafana, and AWS CloudWatch. Mentored a team of junior and mid-level Python developers, conducting code reviews, architecture sessions, and performance audits. Apr 2023 Jul 2025 Implemented unit, integration, and load testing using PyTest, unittest, Selenium, and Locust for backend APIs. Designed and deployed workflow automation systems using Celery, RabbitMQ, and AWS Step Functions. Leveraged AWS EMR and Spark for large-scale data processing and analytics pipelines. Documented system architecture, API specifications, and deployment procedures, improving team onboarding and knowledge sharing.

Senior Python Backend Developer

Developed and maintained Python backend systems using Django, Flask, and Pyramid, supporting large-scale enterprise applications with high availability and low latency requirements. Designed and implemented RESTful and SOAP APIs, integrating with front-end clients (AngularJS, Vue.js, ReactJS) and third-party services to provide seamless data flow. Architected microservices architecture using Python, Docker, and Kubernetes, enabling horizontal scaling and fault-tolerant deployments. Led database design and optimization for PostgreSQL, MySQL, MongoDB, and Cassandra, including indexing, query optimization, stored procedures, triggers, and replication strategies. Built asynchronous and event-driven systems with Kafka and RabbitMQ, enabling real-time data processing pipelines and stream analytics. Implemented serverless workflows on AWS using Lambda, API Gateway, DynamoDB, and Step Functions for event-driven and automated processing tasks. Developed data ingestion and transformation pipelines using Python, Pandas, NumPy, and Spark, handling large-scale structured and unstructured datasets. Integrated machine learning models using TensorFlow, PyTorch, Scikit-learn, and Keras for predictive analytics, NLP, and recommendation engines. Designed and implemented workflow orchestration with Apache Airflow and Celery, ensuring scheduled jobs, retries, and notifications were automated. Developed web scraping and data extraction pipelines using BeautifulSoup and Scrapy, providing structured datasets for internal and external analytics. Implemented authentication and authorization for APIs using OAuth2, SAML, and AWS Cognito for secure user access and role-based permissions. Developed automated CI/CD pipelines using Jenkins, GitHub Actions, ArgoCD, and Ansible for build, test, and deployment automation across environments. Led performance tuning initiatives, optimizing Python code, database queries, and caching layers with Redis, reducing latency by over 30%. Built logging and monitoring solutions using ELK Stack, Prometheus, Grafana, and AWS CloudWatch to proactively monitor system health and reduce mean time to resolution (MTTR). Participated in Agile/Scrum ceremonies, sprint planning, daily standups, and backlog refinement, contributing to architectural decisions and project delivery. Mentored and guided junior Python developers, conducting code reviews, sharing best practices, and improving overall code quality and maintainability. Managed data migrations from relational databases to NoSQL stores like Cassandra for improved scalability and throughput. Implemented Python ORM solutions using SQLAlchemy and Django ORM for efficient data access and abstraction across different database backends. Collaborated with DevOps and cloud teams to automate infrastructure provisioning and scaling using Terraform, CloudFormation, and Ansible. Designed modular Python libraries and utilities to standardize data ingestion, validation, and transformation across multiple projects. Worked on NLP and text analytics projects using NLTK, SpaCy, and OpenNLP to extract sentiment, keywords, and entities from unstructured text. Mar 2017 Apr 2023 Core Skills Programming Languages: Web & Frameworks: Frontend Integration: Cloud & DevOps: Databases: Data & Analytics: Messaging & Workflow: Testing & Automation: Monitoring & Logging: Version Control & Collaboration: Ensured robust testing and validation of backend systems with unit, integration, and regression tests, maintaining >85% test coverage across applications.