Jobs / United States / Airbnb
Senior Analytics Engineer, Airbnb.org
Airbnb · 🇺🇸 United States
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 167 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 71 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 Airbnb paid sponsored hires in similar roles3 certified filings for “Analytics Engineer” (Computer Systems Analysts) in CA: $175k–$200k, median $200k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. 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 — Airbnb
The US Department of Labor certified 167 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 71 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 Airbnb →
About the role
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: In December 2020 Airbnb launched Airbnb.org, a non-profit organization that builds on a long history of connecting people in times of crisis to safe, comfortable places to stay. This work began at Airbnb in 2012, when a Host named Shell reached out wanting to offer her home for free to those impacted by Hurricane Sandy in New York City. Since then, Airbnb - and now Airbnb.org - has helped provide safe housing for over 250,000 people to date in response to hundreds of emergency events around the world including hurricanes, wildfires, refugee crises, and a global pandemic. The Airbnb.org team within Airbnb works in support of the Airbnb.org non-profit and partners with Hosts, nonprofit organizations, emergency management agencies and governments to provide stays to people around the world in times of crisis, and has announced a series of commitments to diversity, equity and inclusion including centering marginalized communities in its work and in team composition. The Difference You Will Make: Airbnb.org operates like a small startup inside Airbnb. Our data team is lean, the problems are new, and there is no established playbook for most of what we do. That means your ingenuity and autonomy are welcome and you will have the room to decide what to build and how, to experiment, and to shape the way a growing, mission-driven organization uses data. Analytics Engineers build the data foundation for the whole team - which translates to impact on all stakeholders with insights, analysis and experimentation. As a Senior Analytics Engineer, you will own major projects that build out the data foundation for Airbnb.org: designing and delivering the data models, metrics and dashboards that power our reporting, analysis and experimentation, and continuously raising the bar on data quality and reliability for the systems you build. Many of these projects will start out vaguely defined, and you will bring structure to them by breaking down the work, weighing tradeoffs, and delivering solutions that are efficient, reliable and simple to maintain. You will bring strong expertise in metric development, dimensional data modeling, SQL, Python, and distributed data processing frameworks, and a solid understanding of how the pieces of a modern data stack fit together. Data can transform how an organization operates; high data quality and tooling is the biggest lever to achieving that transformation. You will partner closely with stakeholders across Marketing, Fundraising, Programs, Product and Engineering to understand their data needs, translate business questions into well-defined metrics and data products, and prioritize your work in line with Airbnb.org's goals. You will work alongside our existing data team - Analytics Engineer, Analyst and Data Scientist - sharing knowledge, seeking and giving feedback, and collaborating with Data Engineering and Data Platform teams to get things built. A Typical Day: • Design, build and launch efficient, reliable and maintainable data models and pipelines that power reporting, analysis and experimentation, in partnership with Data Engineering • Design, define and implement metrics and dimensions for Airbnb.org, and document them clearly so they are trusted and used consistently across teams • Own data quality for the tables and pipelines you build: implement testing, auditing and validation, respond to data incidents, a