Airbnb Senior Data Engineer Interview (L5)
Hiring for Senior Data Engineer at Airbnb (L5) runs Product-sense-heavy with a core-values round that is genuinely decisive. The hiring bar is independent technical leadership and cross-team influence; the median candidate brings 5-8 years of DE experience.
Compensation
$200K–$250K base • $380K–$530K total (L5)
Loop duration
4.8 hours onsite
Rounds
6 rounds
Location
San Francisco, Seattle, remote-first
Compensation
Airbnb Senior Data Engineer total comp
Offer-report aggregate, 2021-2026. Level mapped: L5. Typical experience: 6-8 years (median 8).
25th percentile
$364K
Median total comp
$389K
75th percentile
$428K
Median base salary
$210K
Median annual equity
$158K
Median total comp by year
Tech stack
What Airbnb senior data engineers actually use
Tools and languages mentioned most often in Airbnb's currently-active data engineer postings. Each chip links to an interview prep page for that tool.
IcebergWalk into Airbnb knowing the Python pattern they'll test.
Round focus
Domain concentration by round
What each Airbnb round typically tests, weighted across 2 live senior data engineer postings. The bars show the relative emphasis of each domain.
Online Assessment
Phone Screen
Onsite Loop
Practice problems
Airbnb senior data engineer practice set
Problems written for Airbnb, picked for senior data engineer candidates where the level matches. Each card opens a working coding environment.
One Year to the Next
We want to see how our signup activity spreads across the calendar: for each year, how many separate days actually saw at least one new user sign up, and whether that spread is widening or narrowing year over year. Walking from our earliest year to the most recent, report that yearly count of active signup days alongside the percentage change from the prior year, rounded to the nearest whole percent.
Shortest Unique Metric Tag
A metrics platform stores fully-qualified metric names like 'bookings.checkout.success_rate'. Dashboards autocomplete a metric from any contiguous substring of its name, so each metric needs the shortest substring of its own name that does not appear inside any other metric's name. Given a list of metric names, return a list of the same length where the i-th entry is the shortest contiguous substring of metrics[i] that is not a substring of any other metric in the list. If multiple substrings of the same metric tie for the shortest length, return the lexicographically smallest one. If every substring of metrics[i] also appears in some other metric's name, return an empty string for that metric.
Top Campaign by User Revenue
For each user who clicked an ad, find which campaign generated the most revenue for that user. If multiple campaigns tie for the top, list each qualifying entry only once. Show the user and the top campaign.
Three That Hold
You're auditing a batch of rod lengths pulled from a parts inventory to see how many real triangles could be built from them. Count the groups of three rods that can form a valid triangle, where each side must be shorter than the sum of the other two. Rods sitting at different positions count as separate groups even when their lengths match, and the order of sides within a group does not matter.
Daily signup-to-purchase funnel
Count signups and first-time purchases per day. Product-company favorite.
Roots and Branches
Flat strings carry a hierarchy. Recover it.
Pulled from debriefs where Python parsing was the gate.
The loop
How the interview actually runs
01Recruiter screen
30 minStandard call. Airbnb recruiters probe cultural alignment early, the Core Values round later in the loop can veto strong candidates.
- →Know Airbnb's 4 core values: Champion the Mission, Be a Host, Embrace the Adventure, Be a Cereal Entrepreneur
- →Product sense stories are welcome early, even in a DE track
- →Be specific about the team: Trust, Search, Marketplace, Experiences
02Technical phone screen
60 minSQL + Python. Airbnb SQL is heavy on marketplace / two-sided data: host-guest matching, booking funnels, cancellation patterns.
- →Prepare for marketplace SQL: hosts, listings, bookings, reviews
- →Python problems are practical: data cleaning, anomaly detection
- →Expect ambiguous problem statements, asking clarifying questions is a must
03Onsite: SQL + product analytics
60 minSQL deep-dive with a product-sense layer. 'Define a metric for X. Now write SQL to compute it.' Airbnb cares whether you can translate business questions into data.
- →Practice metric definition: define DAU, define bookings-per-search, define cancellation rate
- →Strong answers include what the metric does NOT capture
- →Be explicit about data-quality assumptions
04Onsite: data system design
60 minDesign a data pipeline for a marketplace-relevant system: search ranking, trust & safety signals, host payouts.
- →Think about both sides of the marketplace, hosts and guests have different data needs
- →Trust & Safety come up often, design for detection of bad actors
- →Cover backfill and historical corrections explicitly
05System design (pipeline architecture)
60 minDesign a production pipeline end-to-end: ingestion, transformation, storage, consumers, SLAs, failure modes, backfill strategy, and cost trade-offs. At senior level, you drive the conversation without prompting. Expect follow-ups about scale, cross-team coordination, and operational load.
- →Anchor on the SLA and data shape before diagramming
- →Discuss idempotency, partitioning, and backfill explicitly
- →Estimate cost: 'This pipeline will cost roughly $X/month at this volume'
06Core values interview
45 minAirbnb's core-values round is famously decisive. Interviewers assess cultural alignment against the 4 values. Technically strong candidates can fail the loop here.
- →Have 2+ stories per core value
- →Champion the Mission is about belonging / travel, frame data work in terms of user trust and experience
- →Be a Host is about empathy, stories about stepping into others' shoes
Level bar
What Airbnb expects at L5 Senior Data Engineer
Independent technical leadership
Senior DEs drive pipeline designs without engineering manager involvement. Interviewers probe whether you can decompose ambiguous requirements, make architecture trade-offs, and defend your choices under scrutiny.
Cross-team coordination
Senior scope regularly spans multiple teams. Expect scenarios about a downstream team missing an SLA because of a change you made, or negotiating a schema migration with the team that owns the upstream source.
Production operational rigor
Fluent in on-call, alerting, data quality checks, and incident response. Dive-deep stories at this level should include correlating a metric drop to a specific commit or a timezone bug or a subtle ordering issue, not 'I looked at the logs.'
Airbnb-specific emphasis
Airbnb's loop is characterized by: Product-sense-heavy with a core-values round that is genuinely decisive. Calibrate your preparation to that, generic FAANG prep will not close the gap on company-specific expectations.
Behavioral
How Airbnb frames behavioral rounds
Champion the Mission
Airbnb's brand mission is belonging. Even DEs are expected to frame their work in terms of user experience and trust.
Be a Host
Empathy and service orientation. Stories about helping colleagues or users through difficulty.
Embrace the Adventure
Comfort with ambiguity and taking on unfamiliar problems. Airbnb wants people who learn fast.
Be a Cereal Entrepreneur
Resourcefulness and scrappy problem-solving. Stories about solving problems without the right tools or sufficient support.
Prep timeline
Week-by-week preparation plan
Foundations and gap analysis
- ·Do 10 medium SQL problems. Note which patterns feel slow
- ·Write out 2-3 behavioral stories per value, Airbnb weights this round heavily
- ·Read Airbnb's public engineering blog for recent architecture patterns
- ·Review your prior production work, pick 3-5 projects you can discuss in depth
SQL and coding fluency
- ·Practice window functions until DENSE_RANK, ROW_NUMBER, LAG, LEAD are reflex
- ·Do 20+ Airbnb-style problems in their domain
- ·Time yourself: 25 min per medium, 35 min per hard
- ·Record yourself narrating your approach aloud. Interviewers weigh how you explain it, not only what you write
Pipeline system design
- ·Design 5 pipelines on paper: daily aggregation, clickstream, CDC, ML feature store, real-time alerting
- ·For each, write SLA, partition strategy, backfill plan, and cost estimate
- ·Practice with a friend, senior-level system design is 50% driving the conversation
- ·Review Airbnb's open-source and engineering blog for in-house patterns
Behavioral polish and mock loops
- ·Rehearse every story out loud. Cut to 2-3 minutes each
- ·Run 2 full mock loops with a senior DE or coach
- ·Identify your 3 weakest behavioral areas and draft additional stories
- ·Review recent Airbnb news or earnings call for fresh talking points
Taper and logistics
- ·No new content. Review your notes only
- ·Sleep. Mental energy matters more than one more practice problem
- ·Confirm logistics: laptop charged, shared-doc tool tested, snack and water nearby
- ·Remember: the loop is rooting for you to raise the bar, not to fail
See also
Other guides you'll want
FAQ
Common questions
- What level is Senior Data Engineer at Airbnb?
- Airbnb uses L5 to designate Senior Data Engineers; this is an IC-track level focused on independent technical leadership and cross-team influence.
- How much does a Airbnb Senior Data Engineer make?
- Airbnb Senior Data Engineer offers span $364K-$428K across 24 samples from 2021-2026, with a median of $389K, median base $210K and median annual equity $158K. Typical experience range: 6-8 years..
- How is the Senior Data Engineer loop different from other levels at Airbnb?
- Senior Data Engineer loops run the same stages as other levels, but interviewers calibrate difficulty to independent technical leadership and cross-team influence, especially around independent system design and cross-team influence.
- How long should I prepare for the Airbnb Senior Data Engineer interview?
- 8-10 weeks is the standard window for a working DE. Less than 4 weeks almost always means cutting the behavioral prep short.
- Does Airbnb interview data engineers differently than software engineers?
- The tracks diverge. DE at Airbnb weights SQL and pipeline-design rounds, and interviewers expect specific production data experience that SWE loops don't probe.
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