Intern Data Engineer, Data Services

IBM

Confirmed live 2 days ago Low trust

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Work type
On-site
Location
—
Employment
Intern
Posted
74 days ago
Freshness
Confirmed live 2 days ago

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How this pay compares to similar roles

Similar $153k
$103k $202k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $114,400–$192,050.

Based on 240 similar postings.

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About IBM

IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

IBM currently has 268 open roles on FindRole.

Listed pay typically runs $187,136–$221,730 across 10 roles with salary data.

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At a glance

TL;DR · Intern Data Engineer, Data Services

As an Intern Data Engineer within the Data Services practice at the IBM Consulting FutureNow Center, you will support organizations in transforming data into actionable insights and unlocking the power of Artificial Intelligence. You will work alongside experienced professionals to design, build, test, and maintain data pipelines, integration processes, and modern data platforms. Your daily tasks include data preparation, transformation, validation, and quality activities to support analytics and automation. You will utilize programming languages such as Python, SQL, and Java, while working with databases, data structures, and cloud technologies. This role addresses the business problem of modernizing data platforms and building scalable environments to enable data-driven decision-making across various industries, including healthcare, financial services, and manufacturing, while focusing on enterprise data architectures and AI-driven solutions.

What does a Data Engineer earn?

Median $159000 from 205 postings across 60 companies.

See salary data

What you'll do

  • Design, build, test, and maintain data pipelines and modern data platforms.
  • Perform data preparation, transformation, validation, and quality assurance for AI solutions.
  • Analyze structured and unstructured data to identify trends and generate business insights.
  • Support data engineering services to improve operational efficiency and data-driven decision-making.
  • Assist in developing and supporting scalable enterprise data architectures and cloud platforms.
  • Participate in project meetings and workshops to develop consulting and communication skills.

What we're looking for

  • High School Diploma/GED.
  • Bachelor's Degree (preferred).
  • Currently pursuing a Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, Statistics, Analytics, or a related field.
  • Interest in data engineering, Artificial Intelligence, analytics, automation, cloud technologies, or digital transformation concepts.
  • Basic understanding of programming concepts and experience with languages such as Python, SQL, Java, or similar technologies.
  • Basic understanding of databases, data structures, data processing, analytics, and how data supports business decision-making.
  • Exposure to data preparation, transformation, visualization, analytics, or business problem-solving through coursework, academic projects, research, hackathons, student organizations, or personal learning.
  • Awareness of Artificial Intelligence, Machine Learning, Generative AI, and emerging technologies, along with their impact on business and digital transformation.
  • Experience gained through academic projects, internships, research, hackathons, certifications, IBMSkillsBuild, student organizations, volunteer experiences, or other practical learning opportunities.
  • Exposure to data engineering, analytics, automation, Artificial Intelligence, cloud technologies, or enterprise data platforms through coursework, student projects, research, hackathons, or internship experiences (preferred).
  • Familiarity with databases, SQL, ETL/ELT concepts, data visualization tools, cloud platforms, machine learning workflows, or modern data architectures (preferred).
  • Interest in Artificial Intelligence, Generative AI, data-driven decision-making, consulting, and continuous learning (preferred).
  • Ability to collaborate effectively with teammates while supporting data modernization, analytics, and enterprise AI transformation initiatives (preferred).

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