Key Responsibilities

Cloud Engineering

• Introduction to Microsoft Azure architecture and core Azure services.

• Assist with deployment and configuration of Azure resources, including App Service, Azure SQL Database, Storage, Key Vault, networking, containers, and monitoring.

• Learn Microsoft Entra ID, managed identities, role-based access control, and least-privilege access.

• Familiarize Azure networking, monitoring, backup, resilience, and disaster recovery concepts.

• Apply existing AWS/GCP cloud concepts to the Microsoft Azure environment.

Infrastructure as Code & DevOps

• Build and modify infrastructure using Terraform.

• Use Git-based source control, branching, pull requests, and code reviews.

• Participate in CI/CD pipeline development using Git.

• Learn DEV, TEST/UAT, and PROD deployment practices, approvals, rollback, and release controls.

• Automate repeatable infrastructure and application deployment processes.

Data Engineering & SQL

• Work with Microsoft SQL Server and Azure SQL.

• Write, troubleshoot, and optimize SQL queries, views, stored procedures, and data transformations.

• Understand relational database design, data modeling, indexing, and query performance.

• Develop ETL/ELT processes using enterprise data sources and APIs.

• Implement data quality, validation, error handling, logging, lineage, and monitoring practices.

• Assist with reporting and analytics solutions.

Application & API Development

• Learn and apply C# and .NET development practices.

• Design, build, consume, and troubleshoot REST APIs.

• Work with authentication, authorization, configuration, secrets, logging, and error handling.

• Build integrations between enterprise applications and data sources.

• Participate in code reviews, testing, troubleshooting, and deployment.

Enterprise IT Operations

• Learn how enterprise applications, databases, integrations, and infrastructure are designed and supported.

• Participate in troubleshooting real application, database, integration, and infrastructure issues.

• Use logs, monitoring, metrics, and diagnostic information to investigate problems.

• Learn change-management and production-support processes.

• Create and maintain clear technical documentation and participate in architecture/project discussions.

Internship Development Expectations

Learn: Understand the company environment, technology stack, development practices, security requirements, and operational processes.

Build: Complete increasingly complex technical assignments with guidance from senior team members.

Own: Take responsibility for a defined project (Sidekick/BRDB Modernization) or component from requirements and design through testing, deployment, documentation, and presentation.

Qualifications

• Currently pursuing a degree in Computer Science, Systems Engineering, Software Engineering, Information Technology, Data Engineering, or a related field.

• Programming experience and working knowledge of SQL and relational databases.

• Understanding of cloud computing, APIs, web application architecture, and Git/source control.

• Strong interest in cloud engineering, data engineering, software development, automation, and artificial intelligence.

• Strong analytical, troubleshooting, written, and verbal communication skills.

• Willingness to learn unfamiliar technologies and ability to work independently while knowing when to ask for assistance.

Preferred Experience

• Python

• SQL

• Docker

• Terraform

• AWS, Azure, or GCP

• ETL/ELT pipelines

• REST APIs

• .NET/C#

• GitHub or Azure DevOps

• Data analytics

• Machine learning or generative AI

What Success Looks Like

• Explain the architecture of key enterprise systems and their major integrations.

• Build and deploy a basic Azure solution and provision cloud infrastructure using Terraform.

• Write and troubleshoot SQL queries and build or modify an API/application component.

• Create and use a CI/CD deployment pipeline.

• Troubleshoot technical problems using logs, monitoring tools, and systematic investigation.

• Understand core enterprise identity, security, secrets-management, and least-privilege concepts.

• Build a practical generative AI or agentic AI solution.

• Produce professional technical documentation and take a small technical project from requirements through deployment.

• Clearly present the design, implementation, lessons learned, and business value of completed work.

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