Software Engineer III

Data Engineer / Full Stack Engineer (Python, Django, Nuxt, AWS)

Position Summary

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.

Key Responsibilities

• 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 TypeScript .



• 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 , NumPy , 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 EventBridge .



• Build and support serverless applications using AWS Lambda and Mangum (ASGI adapter) .



• Manage caching and session layers using Redis / ElastiCache .



• 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 GitHub 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 .

Required Technical Skills

Backend Development

• Python, Django, Django REST Framework (DRF)



• 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



• PostgreSQL 14 (relational database design, query optimization)



• Pandas/NumPy for data processing and transformation pipelines



• OAuth/MSAL integration (Azure AD via django-auth-adfs, MSAL)



• Modular adapter patterns for structured data entities

Frontend Development

• Nuxt 4 (Vue 3, TypeScript), Server-Side Rendering



• Pinia for state management



• Tailwind CSS 4 and Nuxt UI 3 component library



• Azure MSAL Browser for frontend authentication



• Vitest for unit testing, Playwright for E2E testing

Data Engineering

• 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

Cloud & Infrastructure (AWS)

• AWS CDK (Python) and Terraform for Infrastructure as Code



• AWS services: Lambda, SQS, SNS, S3, RDS (PostgreSQL), ElastiCache (Redis), CloudFront, ALB, ECR, VPC networking, WAFv2, Route 53, EventBridge



• Docker containerization and ECR image management



• CI/CD with GitHub Actions (automated deployments, test suites)

Testing & Quality

• 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., SonarQube)

Collaboration & Process

• Git/GitHub workflows and code review practices



• Experience working in distributed Agile teams



• Event-driven design patterns



• Familiarity with cloud-based infrastructure and serverless patterns

Preferred / Bonus Skills

• SAS experience (statistical analysis, data processing)



• Experience with OpenAPI specification and API documentation



• AWS security best practices (IAM, Secrets Manager, WAF)



• Experience with encrypted field storage and credential management

Ideal Candidate Profile

The 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.

Compensation 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:

The minimum full-time salary range is between $80,000 - $90,000

This position is eligible to participate in an annual incentive program, and information on benefits offered is here.

Applications will be accepted through 17th August 2026. This window may be extended depending on business needs.

Who we are:

At Pearson, our purpose is simple: to help people realize the life they imagine through learning. We believe that every learning opportunity is a chance for a personal breakthrough. We are the world's lifelong learning company. For us, learning isn't just what we do. It's who we are. To learn more: We are Pearson.

Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are based on qualifications, merit and business need. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

If you are an individual with a disability and are unable or limited in your ability to use or access our career site as a result of your disability, you may request reasonable accommodations by emailing TalentExperienceGlobalTeam@grp.pearson.com.

Job: Engineering

Job Family: TECHNOLOGY

Organization: Assessment & Qualifications

Schedule: FULL_TIME

Workplace Type: Remote

Req ID: 26118

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