Data Engineering at Airbnb
Roles, Comp & Culture
An L6 staff data engineer at Airbnb sits around $506K total comp from 19 verified salary datapoints. The primary Data Engineering tech consists of Spark, Iceberg and S3, according to current job listings. Airbnb pays data engineers above the other companies we track. Reviews put them at 4.0 on Glassdoor, a little above the middle of the pack. Employee sentiment at Airbnb reads neutral and employee happiness has held flat over the past year. Layoff risk scores low for the next 30 days. 4 data engineering roles are open right now.
Airbnb
Travel · San Francisco, US · ABNB
live data · August 2, 2026
DE total comp
$506K median
L6 · staff level · $464K–$541K · 6 verified datapoints
Hiring now
4 open DE roles
live from career pages
Team happiness
Neutral
employee happiness
Layoff risk (30d)
Low
Employee sentiment
4.0 / 5
MixedEmployees
5,001–50,000
Airbnb data engineer compensation
Each level's figure is the median of individual Airbnb offers at that level, so it reflects a typical outcome rather than an average pulled up by a few large packages. Total comp counts base salary plus equity and bonus annualized over the vest, and the range shown is the middle half of offers, with the top and bottom quarters trimmed off.
What the Airbnb signals mean
Airbnb is regarded as a rigorous, product-driven engineering environment with an unusually deep investment in data literacy and experimentation; the trade-off candidates weigh is the breadth of stakeholders a DE serves against the caliber of the data platform and the direct product impact of the work.
Airbnb employee sentiment, tracked weekly
Employee happiness for data engineers over the past year, so you can see which direction it is moving, not just where it sits today.
Recent Airbnb events
Layoffs, leadership changes, and other major moves at the company, with dates.
- Exec departureNov 2025Leadership change
Notable company events we track, with dates.
Airbnb data engineering tech stack
The languages, storage, and processing tools Airbnb data engineers actually work with, grouped by what they do. Tailor your system-design answers to this stack.
SQL
IcebergAirbnb data engineer job openings
A live read on what they are hiring: open roles, recent postings, where, and at what level.
Develop and automate large scale, high-performance batch and streaming data processing systems to power Airbnb’s Guest and Host products, machine learning models, and business insights.
Architect Ecosystems: Lead the design of overarching data architectures that don't just solve today’s batch needs but anticipate future real-time and AI-driven requirements.
Architect and productionize batch and real-time data systems to support various products and business needs.
Practice for the Airbnb loop
Round by round, the problems our model predicts for this company's interview. Rehearse the shapes their panels keep returning to.
Data engineering teams at Airbnb
Which team you interview for shapes the questions. The main DE surfaces:
Search and Discovery
Ranking pipelines, search relevance features, listing quality signals, and personalization data.
Trust and Safety
Fraud detection, identity verification, risk scoring, and trust signals across hosts and guests.
Payments and Financial
Transaction pipelines, pricing models, payout reconciliation, and tax and compliance data.
Data Platform
Airflow infrastructure, Minerva development, data quality tooling, and schema management.
Host and Guest Analytics
Two-sided marketplace metrics, retention funnels, lifetime value models, and engagement tracking.
Pricing and Revenue Management
Dynamic pricing models, demand forecasting, occupancy optimization, and smart pricing features.
What makes Airbnb different
The things about this company that should shape every answer you give.
Airbnb created Apache Airflow
Airflow was born as an internal Airbnb project in 2014 before becoming an Apache top-level project. This means Airbnb's data infrastructure runs on a deeply customized fork with proprietary operators, monitoring, and SLA tooling. The internal engineering culture treats orchestration as a first-class discipline, not just a scheduler.
Minerva is the single source of truth for all metrics
Unlike most companies where metric definitions live in scattered dashboards and notebooks, Airbnb built Minerva to centralize every metric definition. DEs are responsible for registering metrics in Minerva and ensuring pipelines produce data that conforms to these definitions. This changes how you think about pipeline design: output is not just a table, it is a certified metric.
Two-sided marketplace complexity compounds everything
Most data engineering roles deal with one type of customer. At Airbnb, every feature, every metric, and every pipeline must account for both hosts and guests. A cancellation pipeline must update host availability, guest booking history, trust scores for both parties, and financial records. This multiplier effect makes even simple-sounding problems significantly harder.
Data culture is company-wide, not just an engineering initiative
Airbnb invests in data literacy training for all employees. Product managers, designers, and operations staff are expected to query data and interpret experiment results. DEs build infrastructure that serves the entire company, not just analysts. This means you are evaluated on how well you make data accessible, not just how well you build pipelines.
Preparing for the Airbnb loop
The round-by-round process, example questions, and prep plan are on the interview guide.
Airbnb data engineer roles by level
Level-specific pages: the comp, the bar, and what the loop tests at each seniority.
Comp, level expectations, and role-specific prep.
Comp, level expectations, and role-specific prep.
Comp, level expectations, and role-specific prep.
Comp, level expectations, and role-specific prep.
Comp, level expectations, and role-specific prep.
Compare Airbnb with other data engineering employers
How the role, pay, and loop stack up against peer companies.
Prepare at Airbnb interview difficulty
- 01
Reading a solution is not the same as writing one
Every engineer who has frozen on a query they had read a dozen times knows the gap. The only preparation that closes it is producing the answer yourself, under time, before the interview does it for you
- 02
76% of hiring managers reject on the coding task, not the resume
From HackerRank's 2024 Developer Skills Report. Candidates who look strong on paper still fail the live screen if they haven't done timed, executable practice
- 03
5 problem shapes cover 80% of data engineer loops
Dedup, sessionization, top-N-per-group, slowly-changing dimensions, partition tricks. Writing the shapes by hand turns the unfamiliar into pattern recognition