Software Engineer III

We are seeking a highly skilled Data Engineer / Full Stack Engineer with strong experience in Python-based backend development, modern frontend frameworks, data engineering, and AWS cloud services . This role will be responsible for building and maintaining scalable applications, data pipelines, APIs, and cloud-native services that support enterprise platforms and automation ecosystems.

The ideal candidate will have hands-on expertise in Django/DRF ,
Nuxt/Vue ,
AWS serverless and infrastructure services , and data transformation frameworks including AWS Glue . This individual should be comfortable working across backend systems, frontend applications, cloud infrastructure, and data engineering workflows in a distributed Agile environment.

• Design, develop, and maintain scalable backend services using Python, Django, and Django REST Framework (DRF) .
• Build and document RESTful APIs using DRF / OpenAPI / Swagger .
• Implement robust data validation and API response modeling using Pydantic .
• Develop secure authentication and authorization mechanisms using django-rest-knox ,
  OAuth , and MSAL/Azure AD integrations .
• Create and maintain modern frontend applications using Nuxt 4, Vue 3, and Type Script .
• Manage frontend state using Pinia and build responsive UI solutions with Tailwind CSS and Nuxt UI .
• Design and optimize data engineering pipelines for ingestion, transformation, validation, and delivery of structured and semi-structured data.
• Build and support ETL/ELT workflows using AWS Glue ,
  Pandas ,
  Num Py , and other transformation tools.
• Develop data transformation processes to improve data quality, consistency, and downstream usability.
• Implement event-driven and asynchronous architectures using AWS SQS, SNS, Lambda, and Event Bridge .
• Build and support serverless applications using AWS Lambda and Mangum (ASGI adapter) .
• Manage caching and session layers using Redis / Elasti Cache .
• Design and optimize relational database solutions with PostgreSQL 14+ , including schema design, indexing, and query performance tuning.
• Develop reusable and modular adapter patterns for structured data entities and integrations.
• Provision and manage cloud infrastructure using AWS CDK (Python) and Terraform .
• Support containerization and deployment workflows using Docker and Amazon ECR .
• Build and maintain CI/CD pipelines with Git Hub Actions , including automated testing and deployment.
• Ensure software quality through unit, regression, functional, and load testing practices.
• Participate in code reviews , architecture discussions, and Agile ceremonies with distributed teams.
• Follow AWS security and operational best practices, including IAM, Secrets Manager, WAF, and secure credential handling .

• Pydantic for data validation and API response modeling
• RESTful API design with DRF (OpenAPI/Swagger documentation)
• Token-based authentication using django-rest-knox
• Asynchronous processing with AWS SQS message queues and Lambda event sources
• Serverless architecture using AWS Lambda with Mangum (ASGI adapter)
• Redis for caching and session management
• Pandas/Num Py for data processing and transformation pipelines
• Modular adapter patterns for structured data entities

• Pinia for state management
• Tailwind CSS 4 and Nuxt UI 3 component library
• Vitest for unit testing, Playwright for E2E testing
• Data engineering experience with batch and event-driven data pipelines
• Hands-on experience with AWS Glue
• Strong background in data transformation, cleansing, normalization, and validation
• Experience building ETL/ELT workflows for analytics and operational use cases
• Ability to work with structured and semi-structured datasets across cloud platforms
• AWS CDK (Python) and Terraform for Infrastructure as Code
• AWS services:
  Lambda, SQS, SNS, S3, RDS (PostgreSQL), Elasti Cache (Redis), Cloud Front, ALB, ECR, VPC networking, WAFv2, Route 53, Event Bridge
• Docker containerization and ECR image management
• CI/CD with Git Hub Actions (automated deployments, test suites)

• pytest / pytest-django for backend testing
• Vitest / Vue Test Utils for frontend testing
• Functional, regression, and load testing within automation-driven ecosystems
• Test coverage tooling and quality gates (e.g., Sonar Qube)
• Git/Git Hub workflows and code review practices
• Familiarity with cloud-based infrastructure and serverless patterns

• SAS experience (statistical analysis, data processing)
• Experience with OpenAPI specification and API…