Senior Python Backend Engineer with Cloud & Microservices

Location:

Plano, TX, 75074

Posted:

April 10, 2026

Contact this candidate

Resume:

Ajay Kumar

Phone: +1-561-***-**** Email: *****************@*****.*** Senior Python Developer

PROFESSIONAL SUMMARY:

Architected and developed scalable backend and full-stack applications using Python, Django, FastAPI, and Flask across insurance, financial, and retail domains, supporting high-volume business operations and real-time transaction systems.

Designed and implemented microservices-based architectures with RESTful APIs, enabling seamless integration between backend services and backend service integrations.

Built and optimized backend systems using Python and SQL, including complex queries, joins, and performance tuning to support data-driven features and efficient database interactions.

Strong foundation in core Python concepts including data structures, algorithms, and space-time complexity to develop efficient and maintainable application logic.

Developed robust REST APIs using FastAPI and Django with proper request/response handling, validation, and error management for scalable and reliable service communication.

Leveraged Docker, Kubernetes, and CI/CD pipelines (Jenkins, GitHub Actions) to build, test, and deploy containerized applications with improved release efficiency and system reliability.

Collaborated closely with frontend teams using ReactJS to design and integrate full-stack features, ensuring seamless interaction between UI components and backend APIs.

Applied clean architecture, design patterns, and best coding practices to build modular, extensible, and maintainable systems while working independently across the full software development lifecycle (SDLC).

Processed and transformed data from multiple sources including JSON, XML, flat files, relational and non-relational databases.

Experienced in building scalable backend systems and ETL pipelines using Python, AWS Glue, and SQL for data-driven applications.

Experienced in building cloud-native backend systems on Google Cloud Platform (GCP) and AWS, with strong understanding of distributed systems, microservices, and real-time integrations.

TECHNICAL SKILLS:

Category

Technologies / Skills

Programming Languages

Python, SQL, Bash, JavaScript, Java (Backend Development, Microservices Understanding)

Python Frameworks

Django, Django REST Framework (DRF), Flask, FastAPI, Celery, SQLAlchemy.

Web & Front-End

HTML5, CSS3, Bootstrap, JavaScript, jQuery, ReactJS, Angular, AJAX

Databases (Relational)

PostgreSQL, MySQL, SQLite, Amazon RDS

Databases (NoSQL & Caching)

Redis, DynamoDB, GCP Databases (Spanner, BigTable – Familiarity)

Search & Indexing

Elasticsearch

Messaging & Streaming

Apache Kafka, RabbitMQ, AWS SQS, AWS SNS, AWS EventBridge

Cloud Platforms

Google Cloud Platform (GCP – BigQuery, Cloud Storage, Pub/Sub), AWS (EC2, S3, RDS, Lambda, API Gateway, CloudWatch, Glue, EMR, ECS, EKS)

Containerization & Orchestration

Docker, Kubernetes, Helm

CI/CD & Version Control

Git, GitHub, Jenkins, GitHub Actions, Terraform, Github Workflows

Testing & Validation

PyTest, UnitTest, Mock, Selenium, Postman, Playwright (UI & API Testing), Moto (AWS Mocking).

Data Processing & Analytics

Pandas, Polars, NumPy, Matplotlib, Plotly, Streamlit, seaborn

Machine Learning & Forecasting

Scikit-learn, XGBoost, TensorFlow (Basic), Prophet, AWS SageMaker

Big Data & ETL

PySpark, AWS Glue, AWS EMR, Hadoop, Hive, ETL Pipelines, Data Transformation

API & Integration

REST APIs, SOAP APIs, JSON, XML, Third-Party API Integrations

Security & Authentication

OAuth2, JWT, AWS KMS, AWS Secrets Manager, TLS/SSL Encryption

Monitoring & Logging

ELK Stack (Elasticsearch, Logstash, Kibana), AWS CloudWatch

Build & Application Servers

Nginx, Apache HTTP Server, Gunicorn, uWSGI

Tools & IDEs

PyCharm, VS Code, Jupyter Notebook, Linux/Unix, Jira, Confluence

Methodologies

Agile/Scrum, Test-Driven Development (TDD), SDLC, Code Review, Branching Strategies

PROFESSIONALEXPERIENCE:

Client: Nationwide Insurance, Murfreesboro, TN Mar 2025 to Present

Role: Senior Python Developer

Overview: Worked on building and modernizing core insurance platforms focused on claims processing, underwriting, policy management, and billing systems. Developed scalable backend microservices to automate claim intake, document processing, fraud detection, and premium computation workflows. Contributed to cloud migration initiatives by transforming legacy systems into AWS-based distributed architectures supporting real-time insurance operations and compliance requirements.

Roles & Responsibilities:

Architected, refactored, and modernized legacy Python backend systems into scalable platforms, improving performance, reliability, and maintainability across production environments handling high-volume workflows.

Designed and developed RESTful APIs using FastAPI and Flask with SQLAlchemy-based database connectivity, ensuring efficient request handling, data consistency, and scalable service integration.

Engineered asynchronous workflows using Python asyncio and event-driven patterns to support concurrent processing, improving system throughput and responsiveness across backend services.

Designed and implemented distributed microservices architectures in a cloud-native environment to support scalable and reliable backend systems.

Managed CI/CD pipelines using Jenkins and GitHub Actions, automating build, test, and deployment processes to ensure reliable and consistent software releases.

Validated APIs and backend services using Python-based testing frameworks (PyTest), ensuring high test coverage, data accuracy, and end-to-end workflow reliability.

Optimized backend performance through database tuning, query optimization, and indexing in PostgreSQL and MySQL, improving API response times under high-load conditions.

Implemented secure authentication and authorization mechanisms using JWT and OAuth2, enforcing enterprise-grade access control across distributed backend systems.

Monitored and supported production systems using AWS CloudWatch, Prometheus, and Grafana, proactively identifying issues, debugging failures, and resolving incidents to maintain system reliability.

Built automation frameworks in Python to streamline backend workflows, API validation, and system processes, reducing manual effort and improving operational efficiency.

Applied clean architecture principles, design patterns, and engineering best practices while leading code reviews and maintaining high-quality, scalable codebases.

Collaborated with cross-functional teams including frontend (ReactJS) and product teams to design and integrate full-stack features aligned with evolving business requirements.

Contributed to AI-enabled platform capabilities by integrating intelligent backend services and automation workflows supporting scalable AI-driven system enhancements.

Built reusable Python-based ETL frameworks and modular data processing packages to standardize transformation logic and improve maintainability.

Developed real-time integration workflows between backend services and downstream systems using event-driven architectures and REST APIs.

Environment: Python, FastAPI, Django REST Framework, PostgreSQL, AWS (Lambda, S3), Celery, Redis, Docker, Kubernetes, Jenkins, GitHub Actions

Client: Fiserv, Brookfield, WI March 2024 to Feb 2025

Role: Python Developer

Overview: Worked on enterprise financial systems handling transaction processing, account reconciliation, risk scoring, and regulatory reporting. Built backend services and data pipelines to integrate banking APIs, process high-volume financial data, and generate real-time analytics. Focused on developing secure, scalable systems that support payment processing, financial insights, and compliance-driven workflows in cloud environments.

Roles & Responsibilities:

Developed financial microservices using Python and Django REST Framework to support real-time account reconciliation workflows, ensuring reliable transaction processing across enterprise banking systems.

Integrated external banking APIs using FastAPI and OAuth2, enabling secure data synchronization and seamless communication between distributed financial systems.

Built and optimized ETL pipelines using AWS Glue, PySpark, and S3, focusing on transformation layers, data validation, and scalable processing of high-volume datasets.

Collaborated with data engineering teams to integrate ETL pipelines with backend services, ensuring consistent data flow and system interoperability across financial platforms.

Optimized ETL job performance using partitioning, caching, and query tuning techniques, improving execution efficiency and reducing processing time for large-scale data workloads.

Utilized Polars and Pandas for high-performance data transformation, enabling efficient processing and analysis of large financial datasets.

Designed data transformation pipelines supporting Risk-Based Quality Management (RBQM), ensuring data accuracy, compliance, and validation across regulatory reporting systems.

Deployed containerized microservices using Docker and AWS ECS, building cloud-native backend and data processing services with high scalability and reliability in distributed environments.

Wrote and optimized complex SQL queries including joins, subqueries, and window functions to enhance performance of financial reporting and reconciliation workflows.

Implemented asynchronous processing workflows using Celery and Redis, enabling efficient background job execution for transaction processing and system operations.

Implemented CI/CD pipelines using Jenkins and GitHub Actions, automating build, testing, and deployment processes, and integrated external data sources such as Bloomberg and Reuters APIs.

Developed data validation and testing frameworks using Great Expectations and large-scale datasets, ensuring data quality, reliability, and consistency across ETL pipelines and backend services.

Environment:Python, Django, Flask, PostgreSQL, PySpark, AWS Glue, AWS EMR, Kafka, XGBoost, NumPy, AWS ECS, AWS EKS, AWS Secrets Manager, JWT, Docker, Terraform, Kubernetes, Helm, ELK Stack, Bloomberg API, Reuters API, Jinja, Jenkins, GitHub, GitHub Actions, REST APIs.

Client: Finish line, Indianapolis, IN Feb 2020 to Dec 2023

Role: Python Developer

Overview: Worked on retail and e-commerce platforms supporting inventory management, order processing, product catalog, and customer transactions. Built backend services to handle real-time inventory updates, payment integrations, recommendation systems, and demand forecasting. Delivered scalable solutions to support high traffic during peak sales while improving customer experience and operational efficiency

Roles & Responsibilities:

Developed inventory tracking and product catalog services using Python, Django, and PostgreSQL to support real-time product visibility and stock consistency across retail operations.

Built backend integration APIs using Django REST Framework and Flask to connect inventory systems, order services, and internal retail management workflows.

Implemented ETL processing using Python, Pandas, and AWS Glue to consolidate regional sales and product data into centralized analytics-ready retail datasets.

Developed optimized SQL queries with joins and aggregations to support inventory analytics, sales reporting, and real-time data retrieval for retail operations.

Designed real-time order processing workflows using AWS Lambda, SQS, and DynamoDB to support high-volume order synchronization and reliable event-driven execution.

Built warehouse automation services using FastAPI and Redis to manage allocation, replenishment, and stock movement workflows for operational inventory efficiency.

Created retail dashboards using Streamlit, Plotly, and PostgreSQL to visualize warehouse stock, order velocity, sales KPIs, and inventory decision metrics.

Developed personalized recommendation services using Python, Scikit-learn, and TensorFlow to enhance customer experience through intelligent product suggestion workflows.

Integrated secure payment APIs using Python and AWS API Gateway to support online transaction processing and backend coordination for e-commerce payment services.

Designed and optimized buy-side e-commerce workflows including cart management, checkout processing, and payment integrations to enhance user experience and transaction reliability.

Built demand forecasting pipelines using Prophet, Pandas, and historical sales data to support retail planning and reduce stockout or overstock scenarios.

Implemented high-performance caching using Django Redis Cache and Redis to improve cart performance, checkout speed, and session responsiveness during peak shopping periods.

Automated deployment pipelines using Jenkins, Docker, and GitHub to support efficient build, test, and release execution across staging and production environments.

Tuned PostgreSQL queries and Django ORM mappings to improve performance of transactional APIs, product lookups, and retail analytics reporting services.

Deployed scalable microservices using AWS ECS with auto-scaling configurations to maintain application availability during heavy retail traffic and seasonal spikes.

Built asynchronous background workflows using Celery and RabbitMQ for order confirmations, shipping updates, and customer notification processing across distributed services.

Enhanced product discovery by implementing Elasticsearch with Django ORM to provide accurate search, filtering, and fast retrieval across large retail product catalogs.

Environment: Python, Django, Flask, PostgreSQL, PySpark, AWS Glue, AWS EMR, Kafka, XGBoost, NumPy, AWS ECS, AWS EKS, AWS Secrets Manager, JWT, Docker, Terraform, Kubernetes, Helm, ELK Stack, Bloomberg API, Reuters API, Jinja, Jenkins, GitHub, GitHub Actions, REST APIs.

Client: FuGenX Technologies, Hyderabad, India Feb 2018 to Dec 2019

Role: Python Developer

Overview: Worked on enterprise web applications and internal workflow systems for managing business data, reporting, and integrations. Developed backend systems and APIs to support ERP modules, reporting dashboards, and third-party data synchronization. Focused on building reliable data-driven applications that improved operational efficiency and reduced manual processing across business functions.

Roles & Responsibilities:

Developed data-driven enterprise web applications using Python, Django, and MySQL to manage internal workflows and streamline business information handling across operational systems.

Built RESTful integration services using Django REST Framework to connect ERP modules, reporting applications, and client-facing backend components with secure API-based communication.

Designed normalized relational database schemas using MySQL and PostgreSQL to support scalable data storage, reporting queries, and application performance improvements.Developed SQL queries, views, and stored procedures to support backend data processing, reporting, and application workflows.

Automated recurring data processing workflows using Python scripts, Pandas, and cron jobs to reduce manual reporting effort and improve operational execution consistency.

Built reporting and visualization features using Django templates and Matplotlib to generate business summaries and present performance data to internal stakeholders.

Integrated third-party services using Python Requests and JSON-based APIs to synchronize application data across departments and improve inter-system communication.

Implemented secure form handling and serialization using Django Forms and DRF serializers to validate user input and protect the integrity of business-critical records.

Developed CRUD-driven business modules using Django ORM, views, and templates to enable maintainable data entry, update, retrieval, and workflow automation features.

Configured and deployed Python web applications using Apache, Nginx, and Linux environments to support stable staging and production application hosting.

Implemented authentication and access control using Django Sessions and JWT tokens to secure user workflows and protect role-based access across enterprise applications.

Built KPI dashboards using Plotly, HTML5, and Bootstrap to give management teams visibility into operational trends, activity volumes, and reporting insights.

Collaborated with QA teams to automate regression scenarios using PyTest and Selenium to improve release confidence and reduce defects across iterative development cycles.

Managed source control and delivery workflows using Git and Jenkins to support CI/CD practices and maintain stable release progression across environments.

Integrated notification services using Python SMTP libraries and Celery scheduling to automate emails, reminders, and system-triggered alerts for users and internal teams.

Improved application responsiveness through SQL optimization and Redis caching strategies, strengthening backend performance for frequently accessed data and reporting workflows.

Environment: Python, Django, Django ORM, MySQL, PostgreSQL, Pandas, Matplotlib, REST APIs, JSON, Apache HTTP Server, Nginx, Celery, Redis, JWT, Docker, AWS EC2, AWS RDS, Selenium, PyTest, Git, Jenkins, Linux, Bootstrap.

Client: Orion Headway Technologies, Mumbai, India Nov 2016 to Jan 2018

Role: Python Developer

Overview: Worked on developing internal business applications focused on employee management, payroll systems, and data entry workflows. Built foundational backend modules and simple APIs to automate manual processes and improve data handling efficiency. Gained hands-on experience in full-stack development, database operations, and deploying web applications in structured team environments.

Roles & Responsibilities:

Developed data-driven enterprise web applications using Python, Django, and MySQL to manage internal workflows and streamline business information handling across operational systems.

Built RESTful integration services using Django REST Framework to connect ERP modules, reporting applications, and client-facing backend components with secure API-based communication.

Designed normalized relational database schemas using MySQL and PostgreSQL to support scalable data storage, reporting queries, and application performance improvements.

Automated recurring data processing workflows using Python scripts, Pandas, and cron jobs to reduce manual reporting effort and improve operational execution consistency.

Built reporting and visualization features using Django templates and Matplotlib to generate business summaries and present performance data to internal stakeholders.

Assisted in writing SQL queries and basic data processing logic to support internal reporting and application data workflows.