Cloud-Native Python Java Application Engineer

YATHARTH PANDAY

Hillsboro, OR C: 408-***-**** Email: ************@*****.*** LinkedIn: /yatharthpanday

PROFESSIONAL SUMMARY:

Application/Software Engineer with 10+ years of experience in Python and Java-based application development, specializing in cloud-native and distributed systems.

Extensive hands-on expertise in AWS cloud services including EC2, Lambda, DynamoDB, RDS, S3, SQS, SNS, CloudWatch, Route 53, ECS/EKS, ALB/ELB, and ElastiCache, with strong focus on highly available, fault-tolerant, and event-driven architectures.

Proven experience architecting and developing high-performance RESTful APIs and microservices using FastAPI, Flask, Django, and Spring Boot for customer-facing, B2B, and enterprise platforms.

Strong background in distributed systems, asynchronous processing, event-driven architecture, and cloud-native design patterns with expertise in scalability, resiliency, observability, and performance optimization.

Automated AWS networking tasks using Python and Boto3, including VPC provisioning, subnet configuration, route table management, and network resource inventory reporting.

8+ years of experience with containerization and orchestration technologies including Docker, Kubernetes, ECS, and EKS, supporting scalable deployments across multi-region cloud environments.

Highly experienced in Infrastructure as Code (IaC) and cloud automation using Terraform and CloudFormation, enabling faster provisioning, deployment consistency, and operational scalability.

Designed and developed secure, scalable backend applications using Python, Django, Flask, and FastAPI, implementing OAuth 2.0 and JWT-based authentication mechanisms for enterprise applications.

Containerized Python applications using Docker and deployed them on Kubernetes, integrating deployments with Maven, Jenkins, and Git-based CI/CD pipelines.

Hands-on expertise building CI/CD pipelines and DevOps automation workflows using Jenkins, GitHub Actions, Git, Bitbucket, and Agile delivery methodologies to accelerate software delivery cycles.

Strong experience with observability, monitoring, and production support using Splunk, SignalFx, CloudWatch, and centralized logging frameworks, enabling proactive monitoring and reduced incident response times.

Skilled in performance engineering, profiling, caching strategies, asynchronous I/O, query optimization, and distributed workload tuning to improve system throughput, latency, and infrastructure efficiency.

Advanced SQL and relational database expertise with PostgreSQL and MySQL, including schema design, stored procedures, triggers, indexing strategies, query optimization, and transactional data processing.

ntegrated SonarQube into CI/CD pipelines to perform continuous static code analysis, identify code smells, improve maintainability, and enforce enterprise coding standards.

Experience developing XML/XSD-based integrations, parser frameworks, and API-driven integration platforms for secure and scalable structured data exchange.

Strong understanding of object-oriented programming, domain-driven design (DDD), test-driven development (TDD), automated testing frameworks, and software engineering best practices.

Experienced in collaborating with product managers, TPMs, architects, and cross-functional business stakeholders to translate complex business requirements into scalable technical solutions and phased delivery roadmaps.

Leveraged AI-assisted engineering tools such as GitHub Copilot and Cursor to accelerate software development, code refactoring, unit test generation, and technical documentation while maintaining strong code review and quality standards.

Familiarity with modern AI/ML-enabled engineering workflows, intelligent automation concepts, and API-driven integrations supporting analytics, recommendation engines, and AI-assisted operational platforms.

Strong communication, leadership, and problem-solving abilities with proven success leading multiple concurrent initiatives and delivering high-quality solutions within aggressive timelines.

Education:

•M.S. (Master of Science), San Jose State University, California, U.S.

•B. Tech (Bachelor of Technology) in Mechanical Engineering, Punjab Technical University, INDIA

Technical Skills:

Operating Systems : Linux, Windows and Mac

Programming Languages : Python, JAVA, SQL, C++, HTML, CSS

Web Technologies/Framework : FastAPI, Spring boot, Kafka, Flask, Django.

Databases : Dynamodb, MySQL, Memcached, MongoDB, PostgreSQL

CI/CD Integration Tools : Jenkins

Technical Skills : OAuth 2.0, JWT, OIDC, SSO, RBAC

AI Tools : GitHub Copilot, Cursor, ChatGPT

Version Control : GitHub and Bitbucket

Defect Tracking : ServiceNow, JIRA, Git, and VersionOne

Tools : VScode, IntelliJ IDEA, PyCharm, Dbeaver, Postman, Bruno

Monitoring Tools : Splunk, SignalFx(SFX), AWS Cloudwatch

PROFESSIONAL EXPERIENCE:

Client: NIKE

Role: Application Engineer (Feb 2021 - present)

Responsibilities:

Architected and owned a microservices platform for shipment lifecycle orchestration, scaling to 20M+ annual shipment events while maintaining 99.95% service availability.

Developed scalable backend applications using Python (Django, Flask, and FastAPI) with AWS Aurora (MySQL/PostgreSQL) as the primary database for Nike's retail and e-commerce platforms.

Automated AWS networking tasks using Python and Boto3, including VPC provisioning, subnet configuration, route table management, and network resource inventory reporting.

Implemented OAuth 2.0 authorization flows to enable secure authentication and authorization across internal applications, third-party services, and RESTful APIs.

Designed and implemented domain-driven REST APIs (Python FastAPI/Flask, Java Spring Boot), reducing end-to-end shipment processing latency by 28% and improving downstream data quality by 23%.

Led AWS infrastructure design across ECS, ALB, SQS, SNS, Lambda, Route 53, and CloudWatch, cutting infrastructure provisioning time by 45% through Terraform/CloudFormation automation.

Built event-driven integrations with Apache Kafka and resilient DLQ retry/replay patterns, increasing message processing success to 99.97% and reducing failed-event backlog by 70%.

Optimized freight cost and audit pipelines, improving cost-calculation throughput by 35% and reducing payment discrepancies by 22%.

Built reusable Python authentication middleware to validate JWT signatures, verify token expiration, manage claims, and enforce role-based access control (RBAC).

Enabled scalable integrations with carriers, 3PL providers, and external logistics platforms through secure event-driven APIs and streaming architectures supporting digital and wholesale fulfillment ecosystems.

Implemented multi-region CI/CD and disaster-recovery-ready release pipelines in Jenkins, improving deployment frequency by 2.3x and reducing change-failure rate by 31%.

Established observability standards with Splunk and SignalFx dashboards, alerts, and SLO tracking, reducing Sev-2/Sev-3 MTTR by 37%.

Developed Python automation scripts to orchestrate Maven build execution, deployment validation, log analysis, and release management activities.

Implemented automated testing using PyTest, integrated with Maven and Jenkins pipelines to execute end-to-end quality checks in multi-language application environments.

Drove API performance engineering (profiling, query optimization, caching, async I/O), improving p95 latency by 24% and reducing compute cost by 18%.

Configured and managed Amazon API Gateway to publish, route, secure, and monitor REST APIs connecting Python-based microservices with downstream enterprise systems.

Built high-performance RESTful APIs using FastAPI and Django REST Framework, integrating seamlessly with AWS Aurora for real-time inventory, order management, and customer data processing.

Containerized Python applications using Docker and deployed them on Amazon EKS (Kubernetes), connecting securely to AWS Aurora through IAM authentication and optimized connection pooling.

Partnered with product, TPMs, and business stakeholders to convert requirements into technical designs and phased deliveries, improving roadmap predictability and on-time milestone delivery to 95%.

Converted UI/UX wireframes into reusable React components, maintaining consistency with Nike's design system and improving development efficiency across multiple applications.

Integrated API Gateway with Python-based microservices and data services, enabling reliable data exchange between applications, product information systems, and enterprise platforms.

Used AI-assisted coding (Cursor, GitHub Copilot) to cut time on repetitive implementation and documentation, improving individual throughput ~15–25% on feature and fix work while keeping code review and acceptance tests as the quality gate.

Built AI-ready event-driven data pipelines using Apache Kafka, enabling real-time shipment telemetry ingestion and downstream analytics for predictive operational insights.

Integrated AI-assisted anomaly detection workflows into freight audit and shipment tracking pipelines, helping identify failed transactions, delayed shipments, and cost discrepancies proactively.

Leveraged AI-assisted development tools including Cursor and GitHub Copilot to accelerate feature development, API implementation, infrastructure automation, and technical documentation, improving engineering productivity by 15-25%.

Collaborated with analytics and data science teams to expose scalable APIs and streaming datasets supporting ML-based forecasting, carrier-performance analytics, and operational optimization initiatives.

Technologies Used:

-Python, JAVA, AWS ECS, Dynamodb, RDS, Dbeaver, FastAPI, FlaskAPI, Springboot, Jenkins, Splunk, SignalFx, Apache kafka, github, AWS SQS/SNS, Lambda, Terraform, Cloudformation, GitHub Copilot, Cursor, ChatGPT

Client: NIKE

Role: Front-end/ Infrastructure Engineer (August 2020 - Jan 2021)

Responsibilities:

Designed and built a carrier web platform for trailer and truck data capture used for tracking and tax-filing workflows.

Developed scalable React SPA frontend experiences and integrated them with backend business-rule services.

Implemented AWS infrastructure with CloudFormation to standardize environments and reduce setup time by 40%.

Built UI and backend microservices to ingest and validate transportation access-number data, improving data completeness by 28%.

Integrated OAuth 2.0 authorization code and client credentials flows to support secure API access between Nike's enterprise applications and third-party logistics platforms.

Developed secure REST API endpoints with OAuth 2.0 scopes and JWT claims-based authorization to protect shipment, inventory, and product information services.

Collaborated with Java development teams by integrating Python microservices into Maven-based enterprise applications, ensuring seamless interoperability across distributed systems.

Developed Python-based automation for AWS infrastructure provisioning and configuration validation, integrating networking workflows with Terraform and CI/CD pipelines to improve deployment consistency.

Gathered portal requirements from end users and stakeholders, translating them into technical designs with lower rework.

Implemented Okta-secured authentication flows across frontend interfaces and service integrations.

Enhanced application usability by implementing accessibility (WCAG), cross-browser compatibility, and performance optimization techniques based on UI/UX design recommendations.

Delivered responsive web interfaces with React, Redux, HTML, and CSS for both company and client-facing users.

Authored non-technical workflow documentation to enable operations teams and reduce dependency on engineering support.

Owned quality gates across unit, integration, regression, and end-to-end testing for each release.

Led production support and bug-fix execution throughout the lifecycle, improving release reliability and user experience.

Collaborated with cloud engineering, DevOps, and application teams on the Nike project to troubleshoot AWS network issues, strengthen cloud security, and improve the reliability and scalability of Python-based applications.

Technologies Used:

-JAVA, React, JSON, HTML, CSS, Redux, JIRA, Jenkins, Github, AWS S3, AWS Cloudfront, Jenkins, Cloudformation, Postman

Client: NIKE

Role: Python Developer (June 2019 - July 2020)

Responsibilities:

Architected and implemented AWS microservices for product trade and classification data, improving service scalability by 35% and reducing processing bottlenecks by 28%.

Built REST APIs and Python microservices to calculate and store tax and controls data, reducing processing turnaround time by 32%.

Integrated microservices with external vendor systems for exchange-rate ingestion, improving rate-update accuracy by 20% and reducing manual intervention by 60%.

Designed sync/async workflows on AWS (Lambda, SQS, SNS) to handle peak loads, increasing throughput by 2.1x while maintaining stable performance.

Developed Python-based ETL and data migration scripts to transfer transactional data from legacy databases into AWS Aurora, ensuring data integrity and minimal downtime.

Developed and maintained microservices using Python, Lambda, DynamoDB, RDS, SQS, SNS, and MySQL for product-classification and compliance pipelines.

Implemented secure connectivity to AWS Aurora using IAM Database Authentication, AWS Secrets Manager, SSL/TLS encryption, and VPC security groups.

Implemented composition-service endpoints that orchestrated multiple backend services, reducing client-side integration complexity and improving response consistency.

Built Python REST interfaces for JSON-based external integrations to exchange product controls and tax data across partner systems.

Developed GraphQL and REST APIs that efficiently retrieved and updated data stored in AWS Aurora, supporting Nike's product catalog and customer management platforms.

Delivered enhancements and modernization for legacy product code, reducing recurring defects by 25% and improving maintainability.

Created comprehensive test plans and automated unit/integration test suites with PyTest, increasing test coverage to 85%+ and reducing release defects by 30%.

Supported production operations for critical services, lowering Sev-2/Sev-3 incident MTTR by 33%.

Developed tax-form generation microservices that reduced end-to-end form creation time to under 10 minutes.

Collaborated with business analysts and stakeholders in Agile Scrum teams to convert business needs into technical deliverables with 95% on-time sprint completion.

Collaborated with cross-functional engineering teams to design, document, test, and maintain API contracts using OpenAPI/Swagger, Pytest, and Postman, ensuring API reliability, backward compatibility, and integration readiness.

Technologies Used:

-Python, AWS Lambda, Dynamodb, RDS, Dbeaver, Jenkins, Github, AWS SQS/SNS, Terraform, Postman

TecHindustan Solutions Pvt. Ltd., Mohali, India (March 2014 – July 2016)

Role: Python Developer

Responsibilities:

•Architected and shipped capabilities for large-scale Python web applications, integrating REST APIs and internal services while improving scalability, maintainability, and release quality.

•Integrated Python applications with relational databases by configuring mysqlclient / MySQL Connector (or MySQLdb—use the library you actually used) and optimizing connection pooling and query patterns.

•Reduced outage risk by implementing structured error handling, logging, and clear escalation paths so failures were detected and communicated quickly.

•Delivered code using test-driven development (TDD), automated CI builds, and Agile practices (sprints, reviews, iterative delivery).

•Designed and coded responsive web UI with HTML/XHTML, CSS, JavaScript, jQuery, Bootstrap, AJAX, and JSON payloads for async updates.

•Integrated external systems via SOAP/XML web services: request/response mapping, schemas, retries, error logging, and reconciliation with the system.

•Sped up XML MySQL ingestion by tuning queries and retries, cutting median batch runtime ~57% and failed/part-retry loads ~35%/month.

•Refactored Python/Django output to validated XML/schema aligned with partners, removed duplicate transform path, defects on that slice down ~45% over 6 releases.

•Supported 24 7 operations across production, QA, and development—monitoring, performance tuning, backup/recovery, and incident response.

Technologies Used:

-Python 2.0, Django 1.4, HTML, CSS, XML, MySQL, JavaScript, JQuery, CSS Bootstrap, Mongo DB, MySQL, Git, Linux, Shell Scripting

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