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Data Engineer Internship Jobs in Houston, TX (NOW HIRING)

Capgemini

Data Scientist

Houston, TX · On-site

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative field. * Minimum of 15 months of professional (non-internship) work ...

New

Schlumberger

Technology Intern

Houston, TX

It's a unique insight into the science, data, engineering, and more that are not only driving SLB, but also pushing the boundaries of what's possible in our industry. Technology internships include ...

Schlumberger

Technology Intern

Houston, TX · On-site

It's a unique insight into the science, data, engineering, and more that are not only driving SLB, but also pushing the boundaries of what's possible in our industry. Technology internships include ...

SLB

Technology Intern

Houston, TX · On-site

It's a unique insight into the science, data, engineering, and more that are not only driving SLB, but also pushing the boundaries of what's possible in our industry. Technology internships include ...

Schnabel

Construction and Engineering Internship

Pearland, TX · On-site

$15 - $19.50/hr

This role reports directly to a Schnabel Engineer. You will also have a mentor that will dedicate ... Field data collection and entering into excel spreadsheets * Quantity take-offs and preconstruction ...

Chevron

2026-2027 Petroleum Engineer Intern

Houston, TX · On-site +1

$10K/mo

... data scientists, and/or software developers. Petroleum engineers develop technical skills in ... Interns will be provided with a mentor to provide guidance on their projects. Positions can be ...

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All JobsData Engineer JobsData Engineer Internship JobsData Engineer Internship Jobs in Houston, TX

Data Engineer Internship information

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How much do data engineer internship jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for data engineer internship in Houston, TX is $24.27, according to ZipRecruiter salary data. Most workers in this role earn between $19.76 and $27.55 per hour, depending on experience, location, and employer.

What is a data engineer internship?

A Data Engineer Internship is a temporary, entry-level role where interns gain hands-on experience in data infrastructure, ETL pipelines, and database management. Interns typically work with large datasets, assist in building data models, and collaborate with data scientists and analysts to ensure efficient data processing. They learn tools like SQL, Python, and cloud platforms while improving data quality and automation processes. This role provides valuable industry experience and prepares interns for full-time data engineering positions.

What types of projects or tasks can I expect to work on during a data engineer internship?

As a Data Engineer Intern, you can expect to assist with building and maintaining data pipelines, cleaning and transforming datasets, and supporting the integration of new data sources. You may also help optimize database performance, troubleshoot data quality issues, and collaborate with data scientists or analysts to ensure data accessibility. Interns often work on real-world projects that offer hands-on experience with tools and technologies common in the industry. This exposure not only builds your technical skills but also provides valuable insights into how data engineering supports business decision-making and analytics.

What are the key skills and qualifications needed to thrive in a data engineer internship, and why are they important?

To thrive as a Data Engineer Intern, you need a solid background in programming (especially Python or Java), SQL, and basic data management concepts, often gained through coursework in computer science, data science, or related fields. Experience with tools like SQL databases, ETL pipelines, and cloud platforms (such as AWS or Azure), as well as familiarity with big data frameworks like Hadoop or Spark, is highly valuable. Strong analytical thinking, attention to detail, and the ability to communicate technical information clearly help interns collaborate effectively within diverse teams. These skills are vital for supporting data infrastructure development, ensuring data quality, and contributing to impactful data-driven solutions.

What does a data engineer intern do?

A data engineer intern assists in designing, building, and maintaining data pipelines and infrastructure to support data analysis and storage. They often work with tools like SQL, Python, and cloud platforms, gaining experience in data processing, database management, and data warehousing under supervision.

What are the most commonly searched types of Data Engineer jobs in Houston, TX?

The most popular types of Data Engineer jobs in Houston, TX are:

What are popular job titles related to Data Engineer Internship jobs in Houston, TX?

For Data Engineer Internship jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Data Engineer Internship jobs in Houston, TX look for?

The top searched job categories for Data Engineer Internship jobs in Houston, TX are:

What cities near Houston, TX are hiring for Data Engineer Internship jobs?

Cities near Houston, TX with the most Data Engineer Internship job openings:

Data Engineer Internship jobs near you
Infographic showing various Data Engineer Internship job openings in Houston, TX as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $50,486 per year, or $24.3 per hour.

Data Scientist

Capgemini

Houston, TX • On-site

Other

Posted 3 days ago

New

Key responsibilities

  • Assist in the design, development, and deployment of AI/ML models, including Generative AI and Predictive AI solutions.

  • Support data collection, cleaning, and preprocessing activities for AI initiatives.

  • Participate in client workshops and presentations, effectively articulating technical concepts to diverse stakeholders.

Capgemini North America rating

7.7

Company rating: 7.7 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

98th of 226 rated it services

Job description

(AI/ML Engineer / GenAI Engineer / Data Scientist)

Houston TX

Overview

Capgemini is seeking an enthusiastic and driven Junior AI-Native Consultant to join our dynamic Energy & Utilities sector team. This role is designed for emerging talent passionate about leveraging Artificial Intelligence to solve complex industry challenges. You will contribute to innovative projects, applying advanced AI/ML techniques to optimize operations, enhance decision-making, and drive digital transformation for our clients.

We are looking for individuals who possess a strong foundational understanding of AI concepts and have a minimum of 15 months of professional experience within the Oracle Field Service Cloud (OFSC), Oil & Gas, or broader Utilities domain. This is a client-facing role that requires excellent communication and problem-solving skills.

Key Responsibilities

  • Collaborate with senior consultants and client teams to identify business challenges and opportunities for AI-driven solutions in the Energy & Utilities sector.
  • Assist in the design, development, and deployment of AI/ML models, including Generative AI and Predictive AI solutions.
  • Support data collection, cleaning, and preprocessing activities for AI initiatives.
  • Work with leading cloud technologies (Azure, AWS, GCP) and their AI/ML services.
  • Utilize platforms such as Databricks, PySpark, and modern AI frameworks.
  • Develop agentic AI workflows and intelligent agents to automate tasks and improve operational efficiency.
  • Participate in client workshops and presentations, effectively articulating technical concepts to diverse stakeholders.
  • Contribute to project documentation, reports, and client deliverables.
  • Develop reusable assets, demos, and solution accelerators.
  • Stay current with emerging AI technologies and industry trends, particularly within the Energy & Utilities landscape.
  • Foster a collaborative environment, actively sharing knowledge and best practices within the team.

Required Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative field.
  • Minimum of 15 months of professional (non-internship) work experience in data science, AI, or machine learning roles.
  • Demonstrable background in the Energy & Utilities sector.
  • Foundational knowledge of Artificial Intelligence, Machine Learning, and Deep Learning concepts.
  • Proficiency in at least one AI-centric programming language (e.g., Python).
  • Experience with:
  • Generative AI concepts (GPT, Claude, LLMs)
  • MLOps, model deployment, and monitoring
  • LangChain and Retrieval-Augmented Generation (RAG) concepts
  • REST APIs, JSON, Authentication, and Integration patterns
  • Deployment tools (Azure DevOps, Docker, AWS ECS/EKS/Fargate) and CI/CD pipelines (AWS CloudFormation, CodeDeploy)
  • Data engineering principles, including SQL and NoSQL databases (e.g., MySQL, MongoDB, Redis)
  • Strong analytical, problem-solving, and critical thinking skills.
  • Excellent communication, presentation, and interpersonal skills, with proven ability to engage effectively in client-facing situations.
  • Ability to quickly adapt to new technologies and thrive in a fast-paced, evolving environment.

Preferred Qualifications

  • Prior experience specifically with OFSC (Oracle Field Service Cloud), or general Oil & Gas industry knowledge.
  • Familiarity with industry-specific tools such as Seeq and historians (e.g., PHD).
  • Experience with any of the following:
  • data visualization tools and techniques
  • Machine Learning frameworks (TensorFlow, PyTorch, scikit-learn)
  • NLP
  • computer vision
  • graph database technology (Neo4J, Ontotext, etc.)
  • JIRA / Confluence
  • Prior project or internship experience in a consulting environment.


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