Facility Data Integration Undergraduate Student
Listed on 2026-02-05
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Engineering
Data Engineer, Data Science Manager
Overview
The Maintenance and Site Services Data Group (MSS-DATA) at Los Alamos National Laboratory (LANL) is seeking a highly talented, motivated undergraduate student for a challenging paid internship for summer 2026. Selected candidate will be provided with a mentor and a data/system integration project for their appointment. MSS-Data Group delivers critical facility data services and is responsible for the planning, coordination, and execution of infrastructure/asset management across the institution and is also responsible for required DOE and NNSA reporting.
WhatYou Will Do
Intern will work on a data/system integration project under mentorship. This paid internship is for summer 2026 with a focus on MSS-Data Group objectives related to facility data services and infrastructure/asset management.
Minimum Requirements- Currently enrolled (12 semester credit hours or full-time equivalent) in an accredited undergraduate degree-granting program (or international equivalent)
- Must have and maintain a cumulative GPA of at least 2.75 on a 4.0 scale (or equivalent)
- Entering first-year students must provide documentation indicating matriculation into an accredited undergraduate degree program
We are seeking a wide variety of computational skills used in a database administration and data analysis environment. Candidates should be pursuing one of the following undergraduate degrees (or substantially equivalent):
Computer Science, Computer Engineering, Computer Systems Analysis, Software Engineer, Electrical Engineering.
- AND knowledge and introductory experience in one or more of the following:
- Cluster Computing and System Administration
- Programming skills (C++, Python, SQL, Perl, JSON, etc.)
- SQL Database management
- Integration and Data transfer via API
- Data Storage
- Computer Networking
- Undergraduate:
Currently enrolled (12 semester credit hours or full-time equivalent) in an accredited undergraduate degree-granting program (or international equivalent) - Must have and maintain a cumulative GPA of at least 2.75 on a 4.0 scale (or equivalent)
- Entering first-year students must provide documentation indicating matriculation into an accredited undergraduate degree program
Onsite/Hybrid:
This position is located in Los Alamos, NM with potential for a hybrid arrangement (partially onsite/partially offsite) from a location within a 2-hour ground commute. Reporting onsite will be regularly required. Hybrid is at the discretion of management and can change with notice. Some interns may work a 9/80 schedule at management discretion.
Note to Applicants:
Required Application Materials (for all intern levels - do not delete):
Current resume;
Current official transcripts;
Personal statement of interest (not to exceed one page).
Due to federal restrictions, certain international citizens are prohibited from accessing facilities that support LANL operations. See the original posting for full details.
Where You Will WorkLocated in Northern New Mexico, LANL is a multidisciplinary research institution engaged in strategic science on behalf of national security. LANL offers a generous benefits package including medical, dental, life and disability insurance, parental leave, retirement contributions, tuition assistance, flexible schedules, and more.
Additional DetailsDirective 206.2 - Employment with Triad requires a favorable decision by NNSA indicating suitability under NNSA Supplemental Directive 206.2. This applies to U.S. citizens; foreign nationals are subject to related DOE requirements. The position does not require a security clearance. Pre-employment drug testing and background checks are required. The laboratory maintains a substance abuse policy including random drug testing.
How to Apply& Help
Equal Opportunity: LANL is an equal opportunity employer. The Laboratory provides accommodations for applicants with disabilities upon request. If you need disability accommodation, email applyhelp or call , opt. 3.
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