Jobs / United States / Gallup INC
Data Engineering Intern — Summer 2027
Gallup INC · 🇺🇸 San Francisco
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 29 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 4 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Gallup INC paid sponsored hires in similar roles1 certified filing for “Senior Data Scientist” (Data Scientists) in CA: $195k–$195k, median $195k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. The pay stated here ($50 per hour) is below what this employer usually pays sponsored hires for this role. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Gallup INC
The US Department of Labor certified 29 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 4 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Gallup INC →
About the role
Apply early for priority consideration. Gallup has limited openings for this internship, and the position will be filled quickly. As a data engineering intern at Gallup, you’ll help build and modernize the data tools, infrastructure and pipelines that enable teams to work with data at scale. Alongside experienced technical leaders, you’ll put your Python and SQL skills to work on meaningful projects while learning best practices, experimenting with modern tools and seeing firsthand how strong data engineering supports better decisions. What You’ll Do During your internship, you will: • Build foundational data tooling and infrastructure designed to scale as the volume and frequency of data grow • Help modernize legacy data pipelines using Python, SQL and Gallup’s evolving data platform • Troubleshoot data quality issues in large, imperfect datasets • Apply data engineering practices to move, transform and validate data across systems • Help build reliable, efficient data workflows • Learn from senior technical leaders who will mentor you on engineering practices, tools and approaches • Collaborate with engineers and interact directly with stakeholders to understand needs and deliver useful solutions • Use AI-enabled development tools to improve the quality and efficiency of your work What You Need • Enrollment in an associate, bachelor’s or graduate degree program in computer science, data engineering, information systems, statistics, math or a related field required • Classroom or work experience writing SQL required, including joins, aggregations and troubleshooting query performance • Classroom or work experience coding in Python for data processing, scripting or automation required • Working knowledge of relational database and data modeling concepts, including schema design and dimensional or star-schema modeling, required • Comfort using AI tools such as Claude, Claude Code or GitHub Copilot to support high-quality, efficient work required • Understanding of ETL/ELT concepts and how data are moved, transformed and validated between source systems and a warehouse preferred • Familiarity with cloud data platforms and warehouses (e.g., AWS, Snowflake, Redshift) preferred • Exposure to pipeline orchestration or transformation tooling such as Apache Airflow, dbt or Apache Spark preferred • Familiarity with version control and collaborative development using Git or GitHub preferred • Enrollment at a college or university within an 80-mile radius of San Francisco, California, required • Anticipated graduation between August 2027 and May 2028 preferred • Availability to work 40 hours per week for 12 weeks during the summer of 2027 required • A commitment to working on-site at Gallup’s San Francisco office Monday through Thursday required, with the option to work remotely on Friday • Eligibility to work in the United States required; this position is not eligible for employment visa sponsorship What We Offer • A full-time summer 2027 internship that pays $45 to $50 per hour • The potential to work up to 20 hours per week during the school year, depending on business demands • The potential for a full-time job offer upon graduation, based on Gallup’s business needs and intern performance What You’ll Experience • Mission-driven work: Make a meaningful difference in the world through work that applies science and technology to important human and organizational problems. • An empowering culture: Collaborate with smart, passionate people who welcome your ideas, perspectives and technical judgment. • Learning and development: Grow your skills through hands-on research, experimentation and exposure to AI systems, extensive data and engineering challenges. • Room to challenge assumptions: Work in an environ