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Data Modeling Internship Jobs in Texas (NOW HIRING)

Trinity Industries

Data Analytics Intern

Dallas, TX · On-site

Trinity Industry is looking for Data Analytics Interns for our office in Dallas, TX . This position ... You will contribute to producing AI-first solutions using large language models, agent frameworks ...

TrinityRail

Data Analytics Intern

Dallas, TX · On-site

Trinity Industry is looking for Data Analytics Interns for our office in Dallas, TX . This position ... You will contribute to producing AI-first solutions using large language models, agent frameworks ...

SpaceX

Data Engineer (Starlink)

Bastrop, TX · On-site

$113K - $136K/yr

... Develop Model Context Protocol (MCP) servers and related interfaces that connect AI assistants ... internship experience applicable) • 1+ years of development experience in Python or another ...

State Farm

Lead Data Scientist - Gen AI

Richardson, TX · On-site

Lead/mentor other data scientists, interns, and other technical work teams * Make strategic ... Assess model performance, investigate changes, and perform model updates as necessary. Why Join Our ...

PROLIM Global Corporation

Snowflake Data Engineer

Plano, TX · On-site

$109K - $131K/yr

Must have completed at least 1-2 academic, internship, personal, or training projects related to ... Familiarity with data warehousing concepts, dimensional modeling, and data pipelines. Behavioral ...

Prolim Global

Snowflake Data Engineer

Plano, TX · On-site

$109K - $131K/yr

Must have completed at least 1-2 academic, internship, personal, or training projects related to ... Familiarity with data warehousing concepts, dimensional modeling, and data pipelines. Behavioral ...

SpaceX

Data Engineer (Starlink)

Bastrop, TX

$113K - $136K/yr

Develop Model Context Protocol (MCP) servers and related interfaces that connect AI assistants ... internship experience applicable) * 1+ years of development experience in Python or another modern ...

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Data Modeling Internship information

What is a data modeling internship?

A Data Modeling Internship is a temporary position for students or recent graduates to gain practical experience in designing and structuring data for use in databases and information systems. Interns typically work with data architects and analysts to create data models, which help organize and manage data efficiently for businesses. This role often involves learning about different data modeling techniques, using specialized software tools, and supporting projects that improve data quality and accessibility. The internship provides valuable exposure to real-world data challenges and prepares individuals for future roles in data management and analytics.

What is the difference between Data Modeling Internship vs Data Analyst Internship?

AspectData Modeling InternshipData Analyst Internship
Required SkillsData modeling, database design, SQL, data warehousingData analysis, Excel, SQL, visualization tools
Work EnvironmentData teams, IT departments, database environmentsBusiness units, analytics teams, reporting environments
Industry UsageTech, finance, healthcare, where data structure design is keyMarketing, finance, retail, focusing on data insights

While both internships involve working with data, a Data Modeling Internship focuses on designing and structuring data systems, whereas a Data Analyst Internship emphasizes analyzing data to generate insights. The choice depends on whether you prefer working on database architecture or data interpretation.

What are the key skills and qualifications needed to thrive as a data modeling intern, and why are they important?

To thrive as a Data Modeling Intern, you need a solid understanding of database concepts, data structures, and proficiency in SQL, often supported by coursework in computer science or data analytics. Familiarity with data modeling tools like ERwin, Microsoft Visio, or Lucidchart, and experience with relational database management systems (RDBMS) are typically required. Strong analytical thinking, attention to detail, and effective communication skills help interns collaborate with teams and translate business requirements into data models. These skills are essential for creating accurate, scalable data models that support efficient data storage, retrieval, and analysis in organizational projects.

What types of projects and responsibilities can I expect during a data modeling internship?

As a Data Modeling Intern, you can expect to work closely with data engineers and analysts to design, build, and refine data models that support business intelligence and analytics initiatives. Typical responsibilities include gathering requirements, creating entity-relationship diagrams, normalizing databases, and assisting in the documentation of data flows. You'll also have opportunities to participate in meetings with cross-functional teams, learn best practices for database design, and contribute to ongoing data quality improvement efforts. This hands-on experience provides valuable exposure to real-world data challenges and helps build a strong foundation for a career in data management.
What are the most commonly searched types of Data Modeling jobs in Texas? The most popular types of Data Modeling jobs in Texas are:
What cities in Texas are hiring for Data Modeling Internship jobs? Cities in Texas with the most Data Modeling Internship job openings:
Data Modeling Internship jobs near you

Data Scientist, Smart Maintenance, & Equipment Reliability

Patterson-UTI

Houston, TX • On-site

Full-time

Re-posted 11 days ago

Patterson-UTI rating

5.0

Company rating: 5.0 out of 10

Based on 23 frontline employees who took The Breakroom Quiz

81st of 86 rated oil and gas companies

Job description

As a Data Scientist for the Smart Maintenance initiative, you will support the creation of digital twins and predictive job models to reduce operational uncertainty and strengthen uptime during dynamic operations. You will help modernize maintenance and failure workflows to uncover subtle trends that traditional evaluations may miss, helping the company pursue a meaningful asset-life advantage. By moving data automatically across systems and removing reliance on manual reconciliation, you will help build a foundation for real-time maintenance management and total cost of ownership visibility. Your work will empower field teams with consolidated, purpose-built data that transforms every intervention into a precise, closed-loop maintenance event.

Key Responsibilities:

  • Support the development of predictive models and automated tracking tools to help maintenance teams shift from reactive to proactive workflows.  

  • Assist in the integration of equipment telemetry and various data streams into modeling frameworks to improve lifecycle management.  

  • Help build and test internal AI-driven tools and trend models to streamline technical troubleshooting and root cause analysis.  

  • Contribute to the development of cost-visibility models to track equipment spend and total cost of ownership at different fleet levels.  

  • Assist in the rationalization and optimization of equipment alarm systems to improve alert quality and reduce operational noise.  

  • Monitor the impact of system alerts to help transition toward actionable, condition-based maintenance strategies.  

  • Support data integrity efforts by helping to link information across disparate internal systems and work order platforms.  

  • Collaborate on the design of user-friendly interfaces and digital aids that provide field personnel with accurate equipment history and procedures.  

Job Requirements:

  • Prior experience in equipment reliability, predictive maintenance or physics-based modeling in oil and gas

  • Expert programming skills in Python (SciPy, NumPy) for simulation and model development

  • Strong foundation in reliability engineering methods such as root cause analysis (RCA), alarm management KPIs, and failure mode modeling.

  • Strong communication skills with the ability to explain complex models to non-technical stakeholders

  • Ability to manage multiple priorities and deliver results on time

Minimum Qualifications:

  • Bachelor's degree in Mechanical Engineering, Petroleum Engineering, Data Science or related field

  • 0-5 years of experience applying data science modeling or reliability engineering in industrial settings

  • 2+ years building and deploying data-science algorithms on cloud platforms (AWS, GCP or Azure)

  • A basic understanding of maintenance workflows, work orders, and asset hierarchies is required. 

Preferred Qualifications:

  • Prior internship or project experience involving industrial IoT sensor data and predictive maintenance is preferred.

  • Master's degree or higher in a quantitative engineering or physical science discipline

  • Research publications or patents in equipment reliability, preventative maintenance or related areas

The Evolving Oil Field Demands Evolving Service Providers

NexTier is a leading provider of integrated completions that employs sustainable practices and equipment to support our customers' ESG goals while accelerating production in the most demanding US land basins.

Patterson-UTI is committed to a workplace free from discrimination and harassment, offering equal employment opportunities to all individuals regardless of personal characteristics protected by law. Employees are encouraged to report any concerns through multiple channels.


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