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Intern ULT

Job in Fort Worth, Tarrant County, Texas, 76102, USA
Listing for: Ulterra Drilling Technologies, LP
Apprenticeship/Internship position
Listed on 2026-10-13
Job specializations:
  • Software Development
    Azure, Data Engineering
Salary/Wage Range or Industry Benchmark: 20000 - 36000 USD Yearly USD 20000.00 36000.00 YEAR
Job Description & How to Apply Below
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 , 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 & Dev Ops
  • 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#

  • Git Hub or Azure Dev Ops

  • 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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