Senior Python Developer - Microservices & APIs

KUSUMA

+1-614-***-**** **********@*****.*** www.linkedin.com/in/kusumapy

PROFESSIONAL SUMMARY

•Senior Python Developer with 8 years of experience in architecting, designing, and developing scalable web applications, RESTful APIs, and microservices using Python and modern frameworks like Django, FastAPI, and Flask.

•Proven expertise in asynchronous programming with Celery, RabbitMQ, and Redis, and extensive experience building robust, secure APIs with OAuth2/JWT authentication. Strong background in cloud computing (AWS, Azure), containerization with Docker, orchestration with Kubernetes, and Infrastructure as Code using Terraform and CloudFormation.

•Skilled in CI/CD pipelines with GitLab CI/Jenkins, test automation (PyTest, unittest), database design and optimization (PostgreSQL, MySQL, NoSQL, MongoDB, Azure Data Studio), and real-time data streaming.

•Demonstrated ability to collaborate in Agile/Scrum teams, mentor junior developers, conduct code reviews, and deliver high-quality, maintainable software in distributed environments. Passionate about writing clean, modular, and testable code following PEP8 and industry best practices

•Expert in ORM frameworks such as Django ORM and SQLAlchemy, with extensive experience in integrating relational databases like PostgreSQL, MySQL, and SQLite to efficiently manage data models and optimize complex queries.

•Skilled in managing both relational and NoSQL databases, including Oracle, MySQL, PostgreSQL, MongoDB, Redis, and DynamoDB, with a focus on optimizing performance and handling unstructured data.

•Proficient in writing and optimizing SQL queries, stored procedures, functions, packages, tables, views, and triggers, particularly in relational databases such as Oracle and MySQL.

•Developed and maintained infrastructure as code (IaC) using Terraform to automate the provisioning and management of AWS resources, ensuring consistency and repeatability across environments.

•Strong expertise in data processing, analysis, and visualization, with extensive experience in building ETL pipelines using Python libraries like Pandas, PySpark, and Apache Airflow for large-scale data transformation and reporting.

•Deep expertise in Python core concepts and Object-Oriented Programming (OOP) principles, such as Inheritance, Abstraction, Polymorphism, and Encapsulation, and proficient in areas such as Generators, Decorators, Context Managers, and advanced data structures.

•Well-versed in DevOps practices, including CI/CD pipelines using tools like Jenkins, GitHub Actions, Docker, and Azure DevOps to automate deployment, testing, and monitoring workflows.

•Utilized Docker for containerization and orchestration of microservices, ensuring high availability, scalability, and efficient resource management.

•Used SciPy for advanced scientific and technical computing, including optimization, integration, and signal processing tasks.

•Proficient in working with messaging queues and data streaming platforms, including Apache Kafka, RabbitMQ, and Celery for real-time communication and distributed task processing.

•Experienced in Python software development with expertise in utilizing key libraries like Pandas, SQLAlchemy, Pytest, API, and MySQL Connector to manage data frames, develop APIs, and interact with databases seamlessly.

•Managed Python dependencies and environments with Poetry, ensuring reproducible builds and faster onboarding.

•Automated packaging and publishing of Python projects using pyproject.toml and Poetry’s build tools.

CORE COMPETENCIES

Languages: Python, JavaScript (ES6+), SQL

Frontend / Web Technologies: React.js, HTML5, CSS3, SCSS, JavaScript, AJAX, XML, JSON

Backend & Frameworks: Django, Django REST Framework, FastAPI, Flask, Celery, SQLAlchemy, GraphQL, RESTful APIs, asyncio, multiprocessing, threading

Python Libraries: Pandas, NumPy, OpenPyXL, Requests, Pathlib, re, Matplotlib, Scrapy, PyAutoGUI, Selenium

Database: PostgreSQL, MySQL, MongoDB, Redis, Memcached

Cloud: AWS (EC2, S3, RDS, Lambda, ECS, EKS, CloudFormation, IAM, CloudWatch), Azure

DevOps: Docker, Kubernetes, Terraform, Apache, IIS, Gunicorn

CI/CD & Version Control: Git, GitLab, Bitbucket, SVN

Testing & Automation: PyTest, unittest, Selenium, Postman

AI / LLM: LangChain, LangGraph

Machine Learning: Scikit-learn, TensorFlow, PyTorch, OpenCV

API & Security: RESTful APIs, OAuth2, JWT, API Gateway, Webhooks

Architecture & Design Patterns: MVC, Singleton, Dependency Injection

Monitoring & Logging: Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana), Splunk

Development Tools: PyCharm, Visual Studio Code, Sublime Text, MySQL Workbench, DBeaver

Collaboration Tools: Jira, Confluence, Slack, Microsoft Teams, Zoom, Trello, ServiceNow

Tools & Methodologies: Agile/Scrum, Kanban, Waterfall, SDLC

PROFESSIONAL EXPERIENCE

Senior Software Engineer – Walmart, Bentonville - Remote Jun 2025 – Present

•Designed and developed scalable enterprise applications for Walmart’s e-commerce and seller platforms using Python, FastAPI, Django, and React.js, supporting product, item, pricing, partner, inventory, and order-related business workflows.

•Designed Retrieval-Augmented Generation (RAG) solutions using OpenAI embeddings and vector databases such as Milvus to retrieve relevant enterprise context before LLM generation.

•Built document and enterprise-data retrieval workflows that combined vector similarity search with structured data sources to improve relevance and reduce unsupported LLM responses.

•Designed stateful, multi-step AI workflows using LangGraph, implementing nodes, conditional edges, persistent state, branching logic, fallback paths, and tool orchestration.

•Integrated LangChain agents with LangGraph to orchestrate LLM calls, enterprise REST APIs, GraphQL services, SQL databases, and collaboration tools.

•Implemented intent classification, contextual summarization, fallback handling, validation, and AI guardrails to improve safety and reliability when LLM or downstream service calls failed.

•Optimized prompt construction, context selection, token consumption, and output processing to reduce LLM latency and API costs while maintaining response quality.

•Containerized backend, GenAI, and RAG services using Docker and deployed them to AWS EKS/Kubernetes, supporting horizontal scaling, high availability, and consistent runtime environments.

•Implemented Model Context Protocol (MCP) integrations to standardize context and tool access between AI applications and enterprise services.

•Architected independently deployable Python microservices using FastAPI and RESTful design principles, improving scalability and separation of business capabilities across enterprise applications.

•Developed high-performance REST APIs using FastAPI, Pydantic, and SQLAlchemy, implementing standardized request validation, response models, exception handling, and reusable service components.

•Designed complex Pydantic schemas and custom validation rules for deeply nested JSON payloads exchanged between seller-facing applications and backend services.

•Applied multithreading, multiprocessing, connection pooling, and controlled concurrency patterns to improve performance for high-volume workloads.

•Developed React.js components and integrated frontend applications with FastAPI services to provide real-time access to product, seller, pricing, order, and AI-powered functionality.

•Designed and optimized relational data models using PostgreSQL and SQLAlchemy ORM, implementing indexing and query optimization for high-volume transactional workloads.

•Developed and optimized SQL queries and stored procedures supporting application services, operational reporting, analytics, and enterprise data integrations.

•Built large-scale distributed data-processing pipelines using PySpark and Databricks to transform multi-terabyte retail transaction, inventory, pricing, and customer datasets.

•Integrated PySpark workloads with Amazon S3-based data lakes, implementing ingestion, cleansing, transformation, aggregation, and downstream data-delivery processes.

•Integrated AWS SQS with Lambda and backend microservices to support asynchronous and decoupled processing for workloads requiring reliable message delivery.

•Built internal conversational APIs that combined structured enterprise data with LLM-generated responses, allowing employees to retrieve operational information through natural-language queries.

•Integrated chatbot services with Slack APIs, enabling users to query business-critical data and receive context-aware responses directly within collaboration workflows.

•Designed cloud-native integrations using AWS S3, EC2, Lambda, RDS, ECS, EKS, SQS, Glue, Kinesis, IAM, and CloudWatch for compute, storage, messaging, data processing, and monitoring requirements.

•Supported production incidents and critical business escalations by analyzing logs, service dependencies, event flows, and application metrics and coordinating resolutions across engineering teams.

•Led code reviews and mentored developers on Python, FastAPI, microservices, distributed systems, asynchronous programming, GenAI, and cloud engineering best practices.

Environment: REST APIs, GraphQL, PostgreSQL, Redis, Celery, Apache Kafka, PySpark, Apache Spark, Databricks, Delta Lake, Lambda, RDS, ECS, EKS, SQS, Glue, Kinesis, Docker, Kubernetes, Terraform, GitHub Actions, Jenkins, OpenAI API, LangChain, LangGraph, RAG, PyTest, Prometheus, Grafana, Dynatrace, Git, JIRA, Agile/Scrum.

Full-Stack Python Developer – Verizon, TX Jan 2025 – May 2025

•Built high-performance data pipelines using Snowflake SQL and Snowpark (Python), enabling efficient large-scale data transformations.

•Designed scalable RESTful APIs and async workflows integrated with PostgreSQL and Redis caching, reducing database load and improving system throughput for seller and inventory management services.

•Designed and implemented Snowflake data warehouse solutions, including tables, stages, streams, and tasks for scalable ETL/ELT pipelines.

•Developed incremental data loading strategies using Snowflake streams and tasks, ensuring near real-time data processing.

•Used Dask to process large datasets in parallel, reducing computation time for data pipelines.

•Used Copilot for rapid implementation of AWS integrations (S3, Lambda, RDS) and infrastructure scripts, while leveraging Claude to validate architecture decisions and suggest best practices.

•Integrated Snowflake with AWS S3, Glue, and external stages, enabling seamless ingestion of structured and semi-structured data (JSON, Parquet).

•Designed reusable Pydantic models and schemas for request/response validation, improving data consistency across microservices.

•Utilized Pydantic BaseSettings for managing environment-based configurations, enabling secure and flexible configuration management

•Built background jobs using Celery + Redis for payroll processing and scheduled leave accrual tasks

Environment: Python, FastAPI, Flask, React.js, JavaScript ES6+, Redux, React Hooks, Pydantic, SQLAlchemy, REST APIs, Swagger/OpenAPI, PostgreSQL, Snowflake, Snowpark, Redis, Celery, Dask, AWS S3, Lambda, API Gateway, DynamoDB, Glue, Azure Functions, Azure Cosmos DB, Azure OpenAI Service, Azure Active Directory, Docker, Kubernetes.

Python Full-Stack Developer — Bank of America, NJ Feb 2023 – Dec 2024

•Built reusable Python packages and custom middleware for logging and error tracking.

•Utilized NumPy for high-performance numerical operations, vectorization, and matrix manipulations, reducing data processing time and improving the efficiency of ML and data pipelines.

•Integrated Snowflake with Python and AWS cloud services, leveraging Snowpipe and performance tuning features to enable scalable, cost-efficient data processing.

•Designed API endpoints with DRF, ensuring JWT-based authentication and role-based access control.

•Implemented DynamoDB Streams to trigger event-driven workflows, enabling real-time processing, audit logging, and cross-service synchronization.

•Deployed containerized applications using Docker, orchestrated with Kubernetes clusters on AWS EKS.

•Integrated PySpark with Python libraries like pandas and NumPy for advanced data analysis

•Designed and implemented Apache Kafka-based event-driven pipelines for high-throughput, real-time data streaming between microservices.

•Designed Glue Jobs using Python/PySpark to process large datasets stored in S3, improving data reliability and pipeline performance

•Developed Kafka producers and consumers in Node.js to handle message ingestion, processing, and persistence with guaranteed delivery.

•Monitored Kafka cluster health and performance using Kafka Manager, Grafana, and Prometheus.

•Implemented CI/CD pipelines using GitLab CI and Terraform for infrastructure as code.

•Integrated AWS services like S3, EC2, RDS, CloudWatch, and Secrets Manager.

•Developed Python web applications and microservices using Flask, and FastAPI, implementing modular architecture and reusable components.

•Developed and customized templates and views using HTML/CSS, creating responsive and user-friendly interfaces.

•Developed custom data display and reporting modules, including dynamic dashboards and API-based data aggregation for web pages.

•Configured event-driven workflows using Python signals and event subscribers for tasks such as subscription management and notifications.

•Developed interactive UI components using JavaScript, jQuery, and Python backend APIs for dynamic content and interactivity.

•Implemented custom Python scripts and modules to handle backend logic, automated data processing, and task scheduling.

•Ensured application performance and scalability by conducting regular audits, optimizing database queries, caching, and using asynchronous processing.

•Maintained cloud deployment pipelines using AWS (EC2, S3, Lambda), Docker, and Git, ensuring smooth CI/CD workflows.

•Monitored application health and logs using tools like Prometheus, Grafana, and cloud logging services.

•Managed source control with Git, including branching, merging, and version tracking for multiple environments.

•Tracked tasks, issues, and project backlogs using JIRA, ensuring timely resolution of bugs and feature requests.

Environment: Python, Django, Django REST Framework, FastAPI, Flask, React.js, Redux, JavaScript ES6+, CloudWatch, Docker, Kubernetes, Terraform, Jenkins, GitLab CI, Elasticsearch/Solr, SonarQube, PyTest, Prometheus, Grafana, Git, JIRA, Agile/Scrum.

Python Developer — Value Labs, IND Nov 2020 – Jul 2022

•Led the backend architecture for enterprise applications using Django REST Framework.

•Built reusable Python packages and custom middleware for logging and error tracking.

•Deployed microservices on AWS Lambda and EC2 with auto-scaling groups.

•Built Bash scripts to orchestrate ETL workflows, manage data ingestion, and perform batch processing, enabling seamless integration between databases, cloud storage, and analytics pipelines

•Built prompt pipelines and fine-tuning workflows to customize AI responses for internal business use cases.,

•Designed and maintained high-availability ActiveMQ clusters with failover transport and network connectors.

•Integrated OAuth2 authentication and authorization for secure API access, supporting multiple grant types including Authorization Code, Client Credentials, and Refresh Tokens.

•Implemented JWT-based token generation and verification to secure microservice communication and user sessions.

•Created reusable Bash scripts for application deployment, environment setup, and CI/CD pipeline integration, ensuring consistent builds and faster release cycles across multiple servers

•Used Glue Studio for visual ETL design and Glue Job Monitoring for debugging, logging, and performance insights

•Designed role-based access control (RBAC) and scopes to enforce fine-grained permissions for different API consumers.

•Monitored AI output, logging, and performance using Prometheus and Grafana.

Environment: Python, Django, Django REST Framework, FastAPI, React.js, JavaScript ES6+, HTML5, CSS3, REST APIs, MongoDB, Cassandra, MySQL, Redis, ActiveMQ, Pandas, NumPy, Apache Spark, Spark SQL, PySpark, AWS Glue, AWS, Docker, Kubernetes, Terraform, Jenkins, GitHub Actions, Git, PyTest, Postman, Prometheus, Grafana, JIRA, Confluence, Agile/Scrum.

Python Developer— Incessant Technologies, IND Jun 2018 – Oct 2020

•Interacted with clients and stakeholders to gather requirements, provide feature demos, and incorporate feedback into Python web applications.

•Developed Python scripts and modules to import customer data from XML/CSV formats into databases, ensuring data validation and consistency.

•Built complex features and dashboards using Python frameworks, leveraging modular design patterns for maintainability and scalability.

•Managed master data and taxonomy structures using Python ORM models and implemented business logic to supply and transform functions.

•Designed and implemented custom forms and input interfaces to capture customer data, with backend validation and secure storage.

•Developed custom UI components and themes for dashboards and web pages using HTML, CSS, JavaScript, jQuery, integrated with Python templating engines (Jinja2/Django templates).

•Strengthened security with password validation, CAPTCHA integration, and secure user authentication modules.

•Integrated Airflow with Python scripts, REST APIs, and cloud services AWS to automate end-to-end pipelines.

•Utilized Git for version control, branching, merging, and backup/migration across multiple environments.

•Participated in daily Scrum meetings, updating tasks, discussing blockers, and coordinating with cross-functional teams.

Environment: Python, Django, Django REST Framework, Django ORM, Django Forms, Apache Airflow, JavaScript, jQuery, HTML5, CSS3, REST APIs, JSON, XML, PostgreSQL, MySQL, SQL.

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