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Data Analyst AI Intern

Equinix
Apr 16, 2026

Who are we?

Equinix is the world's digital infrastructure company, shortening the path to connectivity to enable the innovations that enrich our work, life and planet.

A place where bold ideas are welcomed, human connection is valued, and everyone has the opportunity to shape their future.

A career at Equinix means being at the center of shaping what comes next and amplifying customer value through innovation and impact.You'll work across teams, influence key decisions, and help shape the path forward. You'll find belonging, purpose, and a team that welcomes you-because when you feel valued, you're empowered to do your best work.

Role Overview

The AI Data Analyst Intern will support exploration of agentic AI use cases within the design and construction data pipeline. This role focuses on testing "whatif" scenarios, evaluating data quality impacts, and helping understand how AI agents perform individual and collaborative tasks using real construction datasets.

What You Can Expect (Responsibilities & Tasks)


  • Run scenariobased testing to evaluate how data quality and structure affect AI agent outputs
  • Support experimentation with agenttoagent interactions and task specialization
  • Analyze and validate construction datasets using Python
  • Assist with data preparation, comparison testing, and documentation of findings
  • Communicate insights through simple reports, dashboards, or presentations

Why Join Equinix?

Equinix's Global Internship Program offers handson exposure to real business systems in a global enterprise environment.

You will:


  • Work with real production systems and datasets
  • Learn how business analysis, data, and Python scripting support enterprise platforms
  • Gain exposure to applied AI and automation in business operations
  • Receive mentorship, professional development, and access to global intern programming

Who You Are (Requirements & Qualifications)

Required


  • Currently enrolled in an accredited university, in your penultimate year of a Bachelor's degree program
  • Majoring in Information Systems, Business Analytics, Computer Science, Management Information Systems (MIS), Industrial Engineering, Operations, or related fields
  • Expected graduation between December 2026 - September 2027
  • Available to work full-time for the duration of the internship
  • Proficiency in Python for scripting, data analysis, or automation
  • Strong analytical and problemsolving skills
  • Strong written and verbal communication skills
  • Curious, detailoriented, and eager to learn

Preferred


  • Experience using Python libraries
  • Exposure to SQL, databases, or data modeling
  • Familiarity with business systems, APIs, or systems integration concepts
  • Interest or experience with AI tools, automation, or generative AI applications

How to Apply

Please submit:

  • An uptodate resume including

    • Internship availability
    • Expected graduation date


Please apply only if you are available to work fulltime for the full duration of the internship.

Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability. If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form.

Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law.

We use artificial intelligence in our hiring process. Learn more here.

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