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Summer 2027 Data Product Internship

T-Mobile

Bellevue, WAFull-time$27–50/hrPosted 1 day agoStill listed today

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At a glance

Compensation
$27–50/hr
Location
Bellevue, WA
Role Type
Internship
Schedule
Full-time
Work Authorization
Not specified

Olive focuses on jobs in the United States, including remote roles you can work from there.

Job overview

This 11-week paid learning experience places an intern on T-Mobile’s Data & AI team, supporting B2B data products across the product lifecycle. The intern will profile datasets, build dashboards and reporting tables, validate data and pipelines, and support product development. The role includes hands-on projects, training, mentorship, and collaboration with product, engineering, and data science teams.

Skills & qualifications

RequiredNice to have

Skills

Curiosity, nice to haveEvidence-Based Analysis, nice to haveOwnership, nice to haveAttention to Detail, nice to haveAmbiguity Management, nice to haveCollaboration, nice to haveAccountability, nice to haveSQL, nice to havePython, nice to haveData Profiling, nice to haveData Analysis, nice to haveAzure, nice to haveSnowflake, nice to haveStreamlit, nice to haveTableau, nice to havePower BI, nice to haveRelational Concepts, nice to have

Qualifications

Must Be 18+, requiredLegally Authorized to Work in US, requiredCoursework Remaining in Bachelor's or Graduate Program, required

Benefits

Relocation Assistance

Full job description

T-Mobile is synonymous with innovation–and you could be part of the team that disrupted an entire industry! We reinvented customer service, brought real 5G to the nation, and now we’re shaping the future of technology in wireless and beyond. Our work is as exciting as it is rewarding, so consider the career opportunity below as your invitation to grow with us, make big things happen with us, above all, #BEYOU with us. Together, we won’t stop!

Get hands-on experience, training—and a leg up on a bright future.

T-Mobile didn’t become a leader by following the playbook. We got here by breaking it. We’re a disruptor that now plays on a higher tier, and we’re still raising the bar for millions of customers nationwide. If you want to work somewhere that sets the standard instead of matching it, this is your place.

This is an 11-week paid learning experience where you’ll do real work, not busywork. You’ll build relationships with other interns and leaders across the company, and you’ll be paired with mentors who will challenge you to grow skills that matter. We’ll give you hands-on projects with real stakes, and we expect your creativity and sharp ideas to make an immediate impact. You’ll work alongside T-Mobile employees who have your back and who still believe the best ideas can come from anyone.

What It’s Like We’re a hands-on team inside T-Mobile’s Data & AI organization. We cover the full product lifecycle, from market research and prototyping to delivery and support, so you’ll work with product, engineering, and data science. We move fast and help one another. We hold high standards without a culture of fear. A typical week mixes digging into new datasets, building dashboards, chasing down anomalies, and sharing findings with the team.

What You’ll Do You’ll work with large, diverse datasets that power T-Mobile’s B2B data products, which open new markets and revenue streams beyond traditional wireless. You’ll profile new data, document what it can do, and build the dashboards and reporting tables that keep our products accurate, complete, and reliable. Your work will help us bring new products to market faster and keep T-Mobile ahead.

Key Responsibilities

  • Profile and document large datasets, producing data dictionaries that cover schemas, field definitions, completeness, historical availability, and potential use cases.
  • Build and maintain interactive dashboards and reporting tables that track data completeness, enrichment progress, quality metrics, and product performance.
  • Validate datasets and processing pipelines by reconciling record counts, verifying historical backfills, and investigating anomalies, then document your findings.
  • Handle sensitive and proprietary data responsibly.
  • Support product development through requirements, exploratory analysis, feasibility assessments, and rapid prototyping of new data products.

What It Takes

  • Curiosity and a habit of questioning unexpected results. You investigate, explain, and draw evidence-based conclusions instead of just reporting discrepancies.
  • Urgency and ownership. You keep a steady pace without micromanagement and see work through to completion.
  • Thoroughness and attention to detail, especially on repetitive or detail-heavy work.
  • Comfort with ambiguity. You can take a loosely defined assignment, set a clear scope, and deliver outcome-based results.
  • Collaboration and accountability. You ask questions instead of guessing, raise issues early, and focus on root causes instead of blame.
  • Skills in SQL, Python, and data profiling and analysis. Experience with Azure, Snowflake, Streamlit, Tableau, or Power BI is a plus, as is a working knowledge of relational concepts (primary and foreign keys, schemas, data mapping).

Minimum Qualifications

  • At least 18 years of age
  • Legally authorized to work in the United States now and in the future
  • Must have one or more course(s) remaining in a Bachelors or Graduate degree program post internship
  • Employees of T-Mobile or Metro by T-Mobile are ineligible for external Summer Internships, please see Magenta Accelerator if interested

Relocation assistance will be provided to program participants who reside more than 50 miles from the internship location.

Intern wages range from $27/hour to $50/hour. The successful candidate’s actual pay will be based on education/STEM vs non-STEM designation.

Never stop growing! As part of the T-Mobile team, you know the Un-carrier doesn’t have a corporate ladder–it’s more like a jungle gym of possibilities! We love helping our employees grow in their careers, because it’s that shared drive to aim high that drives our business and our culture forward. By applying for this career opportunity, you’re living our values while investing in your career growth–and we applaud it. You’re unstoppable! T-Mobile USA, Inc. is an Equal Opportunity Employer. All decisions concerning the employment relationship will be made without regard to age, race, ethnicity, color, religion, creed, sex, sexual orientation, gender identity or expression, genetic information, national origin, religious affiliation, marital status, citizenship status, veteran status, the presence of any physical or mental disability, or any other status or characteristic protected by federal, state, or local law. Discrimination, retaliation or harassment based upon any of these factors is wholly inconsistent with how we do business and will not be tolerated. Talent comes in all forms at the Un-carrier. If you are an individual with a disability and need reasonable accommodation at any point in the application or interview process, please let us know by emailing [email protected] or calling 1-844-873-9500. Please note, this contact channel is not a means to apply for or inquire about a position and we are unable to respond to non-accommodation related requests.

How this job compares

Set against the 552 open Data Analysis jobs on Olive Jobs, counted November 13, 2026.

Pay
  • This posting$27–50/hr
  • US median$24–40/hr89 hourly ranges

This range's midpoint, $38.50/hr, is 12% above the US median midpoint ($34/hr) — in the middle half of Data Analysis hourly ranges across the US.

Openings
Olive Jobs lists 24 open Data Analysis jobs in Washington and 552 across the US. 5% of them nationwide are listed as remote or flexible.
Hiring the most in Washington
Experience
Data Analysis postings that state a minimum ask for 4 years of experience at the median; the middle half ask for 2 to 5 years (345 postings).
Education
193 of the 552 open Data Analysis jobs (35%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 13, 2026. Figures based on too few postings are left out.

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