招聘
必备技能
Machine Learning
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:
Marketplaces Data and AI is a group of passionate machine learning, software, data, and analytics engineers. We are responsible for developing new, cutting-edge AI and data products that leverage Airbnb’s massive datasets across Users, Listings, Pricing, and Supply/Demand. You will be a crucial part of the Guest and Host organization, building the intelligence that powers the web and native apps used by hundreds of millions of guests and hosts globally.
The Difference You Will Make:
You will own some of the most critical data at Airbnb including Users, Listings, and Marketplaces. You will help uplevel Data Engineering practice and foundation while partnering with partner and infra teams to ship data products and ML models. This is a unique opportunity to shape how we develop data products for not just the Users, Listings, and Marketplaces team but also across Airbnb.
You will play a major role in how data is integrated into our Guest and Host products by
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understanding the business and product need
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aligning with software engineers, ml engineers and data scientist on data flow designing the foundational data models and uplevel critical data sources
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building scalable data architectures that push the boundaries on latency and volume of data
A Typical Day:
We are in the middle of tremendous growth and transformation in the data domain, with significant investments into intelligent products powered by Machine Learning. We are seeking product oriented Senior Staff Data Engineers to drive entity models across Users, Listings, and Marketplace and product initiatives across Quality, Merchandising, and Supply growth.
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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.
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Partner closely with infra teams to improve scalability, data governance, and efficiency
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Evangelize high quality software engineering practices towards building data infrastructure and pipelines at scale, collaborate with infrastructure teams to streamline best practices.
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Advocate for high bar for data and engineering quality ensure eng deliverables are reliable, efficient, well documented, testable, & maintainable.
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Design our data models for optimal storage and understanding, with thoughtful dataflows to power critical product and business requirements.
Your Expertise:
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12+ years of relevant industry experience with a Bachelor’s and/or Master’s degree in CS/EE, or equivalent experience, or 9+ years of experience with a PhD
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Experience collaborating with client, backend, ml, analytics teams, product and business partners
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Experience designing and deploying high performance systems with reliable monitoring and logging practices.
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Effectively work across team boundaries to establish overarching data architecture, data flow, and provide guidance to individual teams.
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Strong knowledge of relational databases and query authoring (SQL).
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Strong expertise with Java / Scala / Spark and operating on data at the petabyte scale.
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Excellent communication skills, both written and verbal.
Your Location:
This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.
Our Commitment To Inclusion & Belonging:
Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.
We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process.
We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.
How We'll Take Care of You:
Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.
Pay Range**$244,000—$305,000 USD**
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关于Airbnb

Airbnb
PublicAn online community marketplace for people to list, discover, and book accommodations through mobile phones or the Internet.
5,001-10,000
员工数
San Francisco
总部位置
$75B
企业估值
评价
3.7
10条评价
工作生活平衡
3.2
薪酬
3.5
企业文化
4.1
职业发展
3.0
管理层
2.8
68%
推荐给朋友
优点
Great team culture and colleagues
Flexible work arrangements and remote options
Good benefits and perks
缺点
Work-life balance challenges
Communication issues and lack of direction
Fast-paced and stressful environment
薪资范围
37个数据点
L2
L3
L4
L5
L6
Mid/L4
Senior/L5
L2 · Financial Analyst L2
0份报告
$211,250
年薪总额
基本工资
$84,500
股票
$105,625
奖金
$21,125
$147,875
$274,625
面试经验
2次面试
难度
3.5
/ 5
时长
14-28周
录用率
50%
体验
正面 50%
中性 50%
负面 0%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Interviews
6
Behavioral Interview
7
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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