Senior Python Backend Developer (AWS)

SUMMARY:

Python backend developer with **+ years of experience designing, building, testing, and supporting enterprise applications and cloud-native services.

Built REST and GraphQL APIs and microservices with Python, FastAPI, Flask, Django, SQLAlchemy, and OpenAPI; implemented secure authentication with JWT and AWS IAM.

Hands-on AWS experience with Lambda, API Gateway, Step Functions, DynamoDB, S3, ECS, Glue, SQS, SNS, CloudWatch, EC2, RDS, Redshift, and CloudFormation.

Designed serverless workflows, asynchronous processing, and data pipelines for financial and travel applications; translated business requirements into maintainable backend logic.

Troubleshot production services and data jobs using logs, monitoring, performance tuning, and automated tests; delivered containerized services through CI/CD pipelines.

Proficient in designing and delivering end-to-end cloud-native applications using React, AWS Lambda, and Python, ensuring scalability and performance.

Strong expertise in TypeScript, JavaScript, and Python scripting for building secure and efficient microservices and UI components.

Experienced in developing and managing REST, GraphQL, and WSO2 APIs for seamless system integration and interoperability.

Skilled in AWS cloud services (Lambda, DynamoDB, Redshift, S3, EC2, CloudFormation) and optimizing performance and cost efficiency of serverless applications.

Solid background in SQL design, optimization, and data modeling for scalable transactional and analytical systems.

Adept at working in Agile/Scrum environments, collaborating with business and engineering teams to deliver quality software.

Proven ability to translate business requirements into technical architectures for finance, trading, and data analytics domains.

Proficient in developing web-based applications using Python, Django, Flask, HTML, XML, JSON, CSS, Java Script & AJAX.

Experience in Designing, Architecting and implementing scalable cloud-based web applications using AWS and GCP.

Experience with Build Automation Tool Maven for writing the SCM Tools like Git, GitHub.

Build Back-end support for applications from the ground up using Python, Shell scripts & Perl.

Experienced with PostgreSQL, MySQL, MongoDB, Redis, Docker, Kubernetes, Terraform, Jenkins, and PyTest; comfortable learning new languages and platforms.

TECHNICAL SKILLS:

Operating Systems

Unix, Linux, Ubuntu, Windows.

Programming Languages

Python, SQL, Java, Scala, C, C++, JavaScript, Bash.

Databases

PostgreSQL, MySQL, Oracle, SQL Server, MongoDB, DynamoDB, Redshift, Redis.

Frameworks

FastAPI, Flask, Django, SQLAlchemy, Celery, ReactJS.

Integration Tools

Jenkins, IBM Integration and Web Builder

Web Server

Apache, Node JS, Tomcat, SOAP, Kafka

Defect Tracking

JIRA, Bugzilla, and VersionOne

Cloud services

AWS Lambda, API Gateway, Step Functions, DynamoDB, S3, ECS, Glue, SQS, SNS, CloudWatch, IAM, RDS, EC2, CloudFormation; Azure, GCP.

PROFESSIONAL EXPERIENCE:

USAA, Plano, TX Nov 2022 – Present

Role: Sr. Full Stack Python Developer

Roles & Responsibilities:

Built and maintained Python serverless microservices using AWS Lambda, API Gateway, DynamoDB, and S3 for scalable financial applications.

Designed REST and GraphQL APIs for portfolio analytics and reporting, with JWT and IAM-based access controls.

Designed serverless processing workflows using Lambda, Step Functions, ECS, and S3 for high-volume financial data.

Implemented backend business workflows with Python and Camunda BPM and translated finance requirements into reusable service logic.

Integrated FastAPI and Django services with SQLAlchemy models to simplify data access and schema evolution.

Built RESTful Flask services with SQLAlchemy for financial analytics and improved backend query handling.

Integrated AWS Glue, S3, Athena, RDS, PostgreSQL, and Redshift into ingestion and transformation pipelines.

Optimized DynamoDB and SQL data models and queries for application performance and cost efficiency.

Containerized backend services with Docker and deployed workloads to Kubernetes and AWS ECS.

Implemented CloudWatch monitoring, centralized logging, and automated alerting to improve production visibility.

Troubleshot production Databricks jobs and PySpark pipelines, validating failures, data quality, and performance against SLAs.

Built PyTest validation and unit tests for financial transaction processing and data transformations.

Automated deployments and infrastructure tasks with Jenkins, Docker, Ansible, and AWS CLI.

Collaborated with QA, DevOps, architects, and business teams to deliver secure, maintainable cloud services.

Implemented data cleansing, transformation, and aggregation logic using PySpark DataFrame APIs to prepare data for reporting and analytical needs.

Collaborated with business analysts and data scientists to design data models that support financial risk assessments, fraud detection, and regulatory reporting.

Optimized PySpark jobs through partitioning, caching, and broadcast joins to improve performance on distributed datasets in a Hadoop/Spark cluster.

Integrated PySpark workflows with AWS cloud services (S3, EMR, Glue) to enable secure and scalable data processing.

Built reusable PySpark functions and user-defined functions (UDFs) for domain-specific logic like transaction categorization, interest calculations, and account scoring.

Implemented unit tests and validation checks to ensure the accuracy and completeness of financial data transformations using PyTest and Spark’s testing framework.

Refactored legacy ETL pipelines into scalable Python-based microservices using Pandas, NumPy, and PySpark, improving maintainability and reducing processing bottlenecks.

Built automated PyTest-based validation frameworks to ensure end-to-end data integrity across financial transaction processing systems.

Containerized backend services using Docker and deployed workloads in Kubernetes environments to support scalable cloud-native infrastructure modernization initiatives.

Optimized complex SQL queries and backend workflows for large-scale financial datasets, improving application response time and batch-processing efficiency.

Developed cloud-native quantitative research applications using Python, ReactJS, and AWS services to support signal generation, portfolio analytics, and investment strategy evaluation platforms.

Designed scalable serverless architectures using AWS Lambda, API Gateway, Step Functions, ECS, and S3 to support high-volume financial data processing and analytics workloads.

Implemented data engineering pipelines using AWS Glue, Athena, PostgreSQL, Redshift, and Pandas for ingestion, transformation, and analysis of large-scale investment datasets.

Developed secure microservices and REST/GraphQL APIs supporting portfolio management, equities analytics, and financial reporting systems with JWT and IAM-based authentication.

Worked closely with quantitative analysts, product owners, and cloud architecture teams to validate proof-of-concepts (POCs) and deploy scalable AWS applications into production environments.

Implemented observability and monitoring solutions using AWS CloudWatch, centralized logging, and automated alerting to improve resiliency and operational visibility of cloud services.

Engineered resilient and secure CI/CD pipelines using Jenkins, Bamboo, Bitbucket, Artifactory, Docker, and Ansible to automate testing, deployment, and infrastructure provisioning.

Developed session management and secure authentication integrations using Okta and AWS security best practices to support enterprise-grade financial applications.

Engineered secure automation utilities using Python and Paramiko to execute remote commands, transfer configuration files, and manage Linux-based infrastructure components, improving operational efficiency across environments.

Integrated SQLAlchemy models into existing FastAPI/Django services to unify ORM behavior across microservices, streamline schema evolution, and reduce manual SQL handling.

Developed and optimized Databricks notebooks using PySpark and Spark SQL for large-scale batch data processing, transformation, and validation.

Built ETL pipelines in Databricks to ingest data from cloud storage, apply cleansing and business rules, and load curated datasets for analytics and reporting.

Worked with Delta Lake features including ACID transactions, schema enforcement, partitioning, and time travel to improve data reliability and auditability.

Scheduled and monitored Databricks jobs and workflows, troubleshooting failures and validating data quality across production pipelines.

Deployed Streamlit applications in a Docker container on AWS ECS, ensuring high availability, scalability, and secure API integrations with backend FastAPI services.

Gathered Semi structured data from S3 and relational structured data from RDS and keeping data sets into centralized metadata Catalog using AWS GLUE and extract the datasets and load them into Kinesis streams.

Introduced new features and solved existing bugs by developing code for a cloud-based integration platform (iPaaS) and migrated customer data from legacy iPaaS to AWS.

Environment: Python, FastAPI, Flask, Django, REST, GraphQL, SQLAlchemy, PyTest, AWS Lambda, API Gateway, Step Functions, DynamoDB, S3, ECS, Glue, Athena, SQS/SNS, CloudWatch, IAM, RDS, Redshift, PostgreSQL, Docker, Kubernetes, Jenkins.

Home Away Inc., Austin, TX Jan 2021 – Oct 2022

Role: Sr. Full Stack Python Developer

Roles & Responsibilities:

Engineered asynchronous REST APIs with FastAPI and Uvicorn for high-throughput travel booking services.

Built AWS Lambda, DynamoDB, and S3 modules for booking and payment processing.

Used Step Functions to orchestrate payment, booking, and notification workflows across services.

Integrated SQS and SNS for asynchronous messaging and event-driven processing between microservices.

Designed retry-safe background processing with Celery and RabbitMQ for confirmations and notifications.

Integrated Redis Streams for real-time event pipelines and user activity tracking.

Generated OpenAPI schemas for FastAPI endpoints to improve API documentation and automated testing.

Optimized ORM queries and Redis caching to improve SQL read performance; tuned transactional database queries.

Provisioned consistent AWS environments with CloudFormation and Terraform.

Debugged application issues during QA and UAT and documented APIs, database schemas, and workflows.

Integrated AWS SQS/SNS for asynchronous messaging and event-driven processing between distributed microservices.

Implemented Amazon RDS and Redshift for analytical and transactional data, optimizing performance with partitioning and compression techniques.

Engineered asynchronous REST APIs with FastAPI and Uvicorn, optimizing high-throughput services in the travel booking domain.

Integrated Redis Streams to support real-time event pipelines and user activity tracking.

Designed retry-safe workflows using Celery integrated with RabbitMQ, ensuring durability of email dispatch, payment processing, and booking confirmations.

Tuned ORM queries and added Redis-based caching to boost SQL read operations performance by 35%.

Led sprint planning and estimation sessions, helping prioritize asynchronous architecture migration in legacy services.

Integrated OpenAPI schema generation in FastAPI endpoints, improving documentation and enabling automated testing.

Created feature flags and toggles using Redis-backed services, enabling safe rollouts and A/B testing of key features.

Assisted in QA and UAT testing, debugging issues and refining application functionalities based on stakeholder feedback.

Created comprehensive technical documentation, including API references, database schemas, and system workflows.

Involved in building database models, APIs, and Views utilizing Python to build an interactive web-based solution.

Designed and created backend data access modules using PL/SQL stored procedures.

Design and implemented custom Bash scripts for controlling the data flow from the PostgreSQL database.

Environment: Python, FastAPI, Django, Flask, REST, OpenAPI, AWS Lambda, DynamoDB, S3, Step Functions, SQS, SNS, RDS, CloudFormation, Terraform, Celery, RabbitMQ, Redis Streams, PostgreSQL, PyTest

Johnson & Johnson, Raritan, NJ Oct 2018 – Dec 2020

Role: Python Developer

Roles & Responsibilities:

Developed backend application logic in Python with Flask and Django.

Integrated application services with SQL and MongoDB data stores.

Built Python automation for external API data collection and processing.

Wrote unit tests with PyTest and Python unittest following test-driven development practices.

Processed and queried operational datasets using Pandas and MySQL.

Used HTML, CSS, AJAX, and JSON to design and develop the user interface of the website.

Improved data security and generated reports efficiently by caching and reusing data.

Managed datasets using Pandas DataFrames and MYSQL. Queried the database using the Python-MySQL connector and retrieved information using MySQLdb.

Recorded the online users' data using Python Django forms and implemented test case using Pytest.

Developed the application using the TestDriven methodology and designed the unit tests using Python Unit test framework.

Developed consumer-based features using Django, HTML, and Test-Driven Development (TDD).

Environment: Python, Flask, Django, REST, SQL, MySQL, MongoDB, Pandas, PyTest, Linux.

Staples, Framingham, MA Jun 2016 – Sep 2018

Role: Software Python Developer

Roles & Responsibilities:

Developed Python and Django backend modules for a web-based data management application.

Designed MySQL data models and queries to support application features.

Worked with architects on requirements, application design, and delivery through Agile sprints.

Implemented data processing operations in Python and MapReduce.

Participated in requirements gathering and worked closely with the architect in designing and modeling.

Worked on installing and setting up the channels using Django. Used JavaScript and JSON to update a portion of a webpage.

Performed joins, group by, and other operations in MapReduce using Python.

Followed Agile Methodologies to manage full life-cycle development of the project.

Environment: Python, Django, SQL, MySQL, Linux, Apache, JavaScript.

Sun Software Technologies - India. Feb 2013 – Apr 2016

Role: Associate Software Engineer

Roles & Responsibilities:

Developed Python and Django application modules, including server-side functionality and data access.

Gathered requirements and worked with architects to design and implement application features.

Used Python and MapReduce for data processing tasks.

Implemented Elasticsearch monitoring and worked with vendors to resolve technical issues.

Involved in gathering and analyzing system requirements.

Performed joins, group by, and other operations in MapReduce using Python.

Followed Agile Methodologies to manage full life-cycle development of the project.

Implemented monitoring and established best practices around using Elasticsearch.

Effectively communicated with external vendors to resolve queries.

Environment: Python, Django, SQL, MySQL, Linux, Apache, Elasticsearch, JavaScript.

Education: Bachelor's in Information Technology, JNTUH, 2012.

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