{"id":2309586,"url":"https://alion.io/job/pearsonvue-software-engineer-iii-2","title":"Software Engineer III","company":{"id":94619,"name":"Pearson VUE","domain":"pearsonvue.com","url":"https://alion.io/company/pearsonvue","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":75,"open_postings":18,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-13T05:45:00Z"}},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":80000,"max":90000,"currency":"USD","period":"year","gross":null,"usd_annual":90000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon EventBridge","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS CDK","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Django","optional":false},{"name":"Django REST Framework","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"GitHub Actions","optional":false},{"name":"IAM","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Pinia","optional":false},{"name":"Playwright","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Pydantic","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"SonarQube","optional":false},{"name":"Swagger","optional":false},{"name":"Tailwind CSS","optional":false},{"name":"Terraform","optional":false},{"name":"TypeScript","optional":false},{"name":"Vitest","optional":false},{"name":"Vue.js","optional":false},{"name":"JavaScript","optional":true},{"name":"SAS","optional":true}],"status":"live","first_seen_at":"2026-10-06T13:19:39Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-13T14:00:30Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Data Engineer / Full Stack Engineer (Python, Django, Nuxt, AWS)\nPosition Summary\nWe 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.\nThe 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.\nKey Responsibilities\nDesign, develop, and maintain scalable backend services using Python, Django, and Django REST Framework (DRF).\nBuild and document RESTful APIs using DRF / OpenAPI / Swagger.\nImplement robust data validation and API response modeling using Pydantic.\nDevelop secure authentication and authorization mechanisms using django-rest-knox, OAuth, and MSAL/Azure AD integrations.\nCreate and maintain modern frontend applications using Nuxt 4, Vue 3, and TypeScript.\nManage frontend state using Pinia and build responsive UI solutions with Tailwind CSS and Nuxt UI.\nDesign and optimize data engineering pipelines for ingestion, transformation, validation, and delivery of structured and semi-structured data.\nBuild and support ETL/ELT workflows using AWS Glue, Pandas, NumPy, and other transformation tools.\nDevelop data transformation processes to improve data quality, consistency, and downstream usability.\nImplement event-driven and asynchronous architectures using AWS SQS, SNS, Lambda, and EventBridge.\nBuild and support serverless applications using AWS Lambda and Mangum (ASGI adapter).\nManage caching and session layers using Redis / ElastiCache.\nDesign and optimize relational database solutions with PostgreSQL 14+, including schema design, indexing, and query performance tuning.\nDevelop reusable and modular adapter patterns for structured data entities and integrations.\nProvision and manage cloud infrastructure using AWS CDK (Python) and Terraform.\nSupport containerization and deployment workflows using Docker and Amazon ECR.\nBuild and maintain CI/CD pipelines with GitHub Actions, including automated testing and deployment.\nEnsure software quality through unit, regression, functional, and load testing practices.\nParticipate in code reviews, architecture discussions, and Agile ceremonies with distributed teams.\nFollow AWS security and operational best practices, including IAM, Secrets Manager, WAF, and secure credential handling.\nRequired Technical Skills\nBackend Development\nPython, Django, Django REST Framework (DRF)\nPydantic for data validation and API response modeling\nRESTful API design with DRF (OpenAPI/Swagger documentation)\nToken-based authentication using django-rest-knox\nAsynchronous processing with AWS SQS message queues and Lambda event sources\nServerless architecture using AWS Lambda with Mangum (ASGI adapter)\nRedis for caching and session management\nPostgreSQL 14+ (relational database design, query optimization)\nPandas/NumPy for data processing and transformation pipelines\nOAuth/MSAL integration (Azure AD via django-auth-adfs, MSAL)\nModular adapter patterns for structured data entities\nFrontend Development\nNuxt 4 (Vue 3, TypeScript), Server-Side Rendering\nPinia for state management\nTailwind CSS 4 and Nuxt UI 3 component library\nAzure MSAL Browser for frontend authentication\nVitest for unit testing, Playwright for E2E testing\nData Engineering\nData engineering experience with batch and event-driven data pipelines\nHands-on experience with AWS Glue\nStrong background in data transformation, cleansing, normalization, and validation\nExperience building ETL/ELT workflows for analytics and operational use cases\nAbility to work with structured and semi-structured datasets across cloud platforms\nCloud & Infrastructure (AWS)\nAWS CDK (Python) and Terraform for Infrastructure as Code\nAWS services: Lambda, SQS, SNS, S3, RDS (PostgreSQL), ElastiCache (Redis), CloudFront, ALB, ECR, VPC networking, WAFv2, Route 53, EventBridge\nDocker containerization and ECR image management\nCI/CD with GitHub Actions (automated deployments, test suites)\nTesting & Quality\npytest / pytest-django for backend testing\nVitest / Vue Test Utils for frontend testing\nFunctional, regression, and load testing within automation-driven ecosystems\nTest coverage tooling and quality gates (e.g., SonarQube)\nCollaboration & Process\nGit/GitHub workflows and code review practices\nExperience working in distributed Agile teams\nEvent-driven design patterns\nFamiliarity with cloud-based infrastructure and serverless patterns\nPreferred / Bonus Skills\nSAS experience (statistical analysis, data processing)\nExperience with OpenAPI specification and API documentation\nAWS security best practices (IAM, Secrets Manager, WAF)\nExperience with encrypted field storage and credential management\nIdeal Candidate Profile\nThe ideal candidate is a technically strong engineer who can work across application development, cloud architecture, and data engineering. They are comfortable building APIs, frontend interfaces, serverless systems, and data transformation pipelines, while maintaining strong standards for scalability, security, and software quality.\nCompensation at Pearson is influenced by a wide array of factors including but not limited to skill set, level of experience, and specific location. As required by the California, Colorado, Hawaii, Illinois, Maryland, Minnesota, New Jersey, New York State, New York City, Vermont, Washington State, and Washington DC laws, the pay range for this position is as follows:\nThe minimum full-time salary range is between $80,000 - $90,000\nThis position is eligible to participate in an annual incentive program, and information on benefits offered is here.\nApplications will be accepted through 17th August 2026. 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