Backend Engineer

Role:

We are seeking a Backend Engineer with strong experience in Node.js or Python, Azure services, REST APIs, SQL databases and cloud-native backend development to design and implement backend services for a self-service Data Analysis Platform.

Key responsibilities:

1. Backend API Development

• Design and implement the Portal Backend API using Node.js or Python.
• Develop secure and scalable REST endpoints for engagement management, file management, user and role management, and provisioning workflows.
• Implement robust business logic, validation, error handling and API security.
• Design APIs that support scalable integration with frontend applications and downstream services.
• Maintain clear API documentation and development standards.
• Troubleshoot and optimize backend services for reliability and performance.

2. Azure SQL and Data Modeling

• Design and implement Azure SQL schemas for the shared Portal Metadata Database.
• Develop data models for engagement registries, file catalogs and related platform metadata.
• Design and maintain per-engagement Analytics SQL databases.
• Write efficient SQL queries, stored procedures and data-access logic where appropriate.
• Optimize database queries and schemas for performance and scalability.
• Ensure appropriate data isolation between engagements.

3. Authentication, Authorization and RBAC

• Implement engagement-scoped Role-Based Access Control (RBAC) middleware.
• Integrate backend authentication and authorization with Azure Entra ID using OIDC/OAuth.
• Implement and enforce the platform's three primary roles: admin, practitioner and client.
• Ensure users can access only the engagements and resources for which they are authorized.
• Secure REST APIs and backend services against unauthorized access.
• Implement appropriate permission checks across engagement, file, user and administrative operations.

4. File Storage and Ingestion Services

• Design and implement secure file upload and download services using Azure Blob Storage / ADLS Gen2.
• Implement secure SAS token issuance for controlled file access.
• Support large, multi-GB file uploads with appropriate validation and reliability mechanisms.
• Implement checksum validation and file-integrity verification.
• Design efficient file metadata and catalog management.
• Handle upload failures, retries and other edge cases gracefully.
• Ensure file access follows engagement-level authorization and security policies.

5. Audit Logging and Compliance

• Design and implement a centralized audit logging system.
• Capture data uploads, access events, downloads and administrative actions.
• Ensure audit records contain sufficient information for compliance, security investigations and operational observability.
• Implement secure and reliable storage of audit information.
• Ensure audit logging is integrated consistently across relevant backend services and workflows.

6. Engagement Lifecycle Management

• Implement backend workflows for engagement creation, provisioning, archival and decommissioning.
• Develop provisioning request and approval workflows.
• Trigger automated environment creation and provisioning processes.
• Implement retention policies and lifecycle controls.
• Support controlled teardown and decommissioning of engagement environments.
• Ensure lifecycle operations are secure, auditable and appropriately authorized.

7. Power BI Integration

• Implement backend integration with Power BI for secure client-facing report delivery.
• Integrate with Power BI APIs and supporting services.
• Ensure embedded reports and dashboards are accessible only to authorized users and engagements.
• Implement appropriate authentication, authorization and access-control mechanisms for report delivery.

8. Azure Functions and Asynchronous Processing

• Design and implement Azure Functions for asynchronous and event-driven operations.
• Implement provisioning workflows triggered through Azure Service Bus.
• Develop scheduled functions for lifecycle management and operational tasks.
• Build serverless data-processing pipelines where appropriate.
• Implement reliable processing, retry and error-handling mechanisms for asynchronous workflows.
• Ensure serverless components are scalable, maintainable and observable.

9. AI-assisted Data Processing

• Integrate backend services with Azure OpenAI inference endpoints.
• Support AI-assisted data processing capabilities within the analytics workbench.
• Develop secure API integrations for AI inference workflows.
• Apply appropriate validation, error handling and security controls around AI-assisted processing.
• Collaborate with data and application teams to integrate AI capabilities into backend workflows.

10. Testing and Quality Engineering

• Write comprehensive unit and integration tests for backend services.
• Test REST API endpoints, authentication and authorization middleware, business logic and data-access components.
• Test file upload/download workflows and asynchronous processing.
• Validate security and engagement-scoped access controls through automated tests.
• Maintain adequate regression coverage as platform functionality evolves.
• Identify and resolve defects before production deployment.

11. Code Review and Engineering Practices

• Participate actively in peer code reviews.
• Review pull requests for correctness, security, performance and maintainability.
• Ensure code follows established coding standards and engineering best practices.
• Provide constructive feedback and contribute to continuous improvement of backend development practices.
• Maintain clean, readable, testable and maintainable production code.