Intern ULT
Patterson-UTI
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- Location
- Texas, United States
- Job type
- Internship
- Posted
- Oct 7
- 13 days ago
Career path
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About the company
Patterson-UTI
Oil & energy · 10,001+ employees
What you'll do
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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
- 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.
Key skills
cloud infrastructureapplication developmentdata engineeringDevOpsautomationartificial intelligenceenterprise systems
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Read the full posting here
The Cloud, Data & AI Engineering Intern will work directly with the IT organization on real-world enterprise technology initiatives. The six-month internship is designed to provide broad hands-on experience across cloud infrastructure, application development, data engineering, DevOps, automation, artificial intelligence, and enterprise systems.
The intern will progress from guided learning and small technical assignments to independently owning defined components of production-oriented projects, including design, development, testing, documentation, deployment, and presentation.