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:
People Analytics & Research is a strong team of Data Scientists, Researchers, and Analysts. Our work is highly sought-after, and we prioritize work that impacts employees and the business. If you have a background in Data Engineering and are excited to help build Airbnb’s community, we want to hear from you.
The difference you will make:
The People Analytics & Research team is looking for an experienced Data Engineer to support our growing portfolio of data initiatives — from building data pipelines to delivering data foundations and analytical products that power EX's growing suite of AI-driven tools. Your responsibility spans data infrastructure, analytics engineering, and data product development. The role is highly cross-functional,and you will work with Talent Leaders, Recruiting, Legal, Diversity and Belonging, and other core people-oriented teams, as well as contribute to the AI-driven tools that make people data more accessible across the organization.
Your Responsibilities:
- Collaborate with other team members and stakeholders to help understand data- and people-related business problems and translate them into scalable data solutions
- Build data pipelines and tables from HR systems such as Workday, Greenhouse, and other data sources
- Support Data Science team members in leveraging data for reporting, dashboard development, and other client-facing use-cases
- Build, update, and maintain a production-grade data foundation that supports AI initiatives — including pipelines that feed LLM-powered tools, evaluation and feedback datasets, and the access controls and data models required to responsibly scale AI products from prototype to production
- Design and deliver data products, including dashboards and reporting tools (e.g., Streamlit visualization apps), that surface actionable insights for non-technical stakeholders
- Write and optimize queries across both distributed query engine (Trino/Presto) and private relational database (Postgres)
- Align on priorities and work from a roadmap, ensuring you are focusing on the highest-priority projects
- Assess data readiness for AI use cases, working with EX teams, Legal, and BizTech to ensure sensitive employee data is handled with appropriate governance, permissioning, and access controls
- Support the transition of AI prototypes to production by building the underlying infrastructure — automated pipelines, security controls, and stable data models — that prototypes require to scale
- Exercise traits of adaptability and good judgment to support organizational agility
- Be a constant learner, active listener, and teacher to advance data engineering, people analytics, and Airbnb
Your Expertise:
- 5+ years of industry experience as a Data Engineer, or closely related field
- Highly proficient in SQL across both OLAP and OLTP environments, in both Trino/Presto/Hive, and Postgres syntax.
- Strong command of the Ubuntu environment, showcasing the ability to navigate, manage, and edit files on AWS instances through SSH.
- Experience working with relational databases and the ability to assume an administrative role in managing the database.
- Fluent in Python, with demonstrated ability to interact with data sources (web APIs, SFTP, S3 buckets, Airtable) and efficiently process intermediate data.
- Experience with scalable data pipelines leveraging Airflow or similar scheduling/orchestration frameworks.
- Proficiency in implementing essential database concepts accurately, including primary key, index, nullable fields, data types, and partitioning; experience designing data models for optimal storage and retrieval.
- Prior work experience with sensitive data, including sensitivity classification, access controls, and audit logging; familiarity with data governance requirements for employee or sensitive data.
- Experienced with building data products, dashboards or reporting tools, using light weighted frontend frameworks such as Streamlit, with visualizations that communicate insights to business stakeholders.
- Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, interpret complex queries and effectively communicate findings to non-technical audiences.
- Experience building data layers that support LLM-based tooling or agentic AI frameworks, including data quality and latency requirements for model consumption, AI evaluation practices, and feedback loop and evaluation dataset management.
- Strong comfort working cross functionally, with both technical and non-technical stakeholders.
- Solid understanding in data structures & algorithms, with the ability to make use of data structures to work through medium-complexity problems.
- Knowledge and proficiency in utilizing Git repositories for effective code base management, version control, and the ability to mentor and support peers.
- Familiarity with system design principles, especially as applied to data platforms or AI-integrated systems.
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: [email protected]. 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.
Skills Required
- 5+ years industry experience as a Data Engineer or closely related field.
- Highly proficient in SQL across OLAP and OLTP, including Trino/Presto/Hive and Postgres.
- Strong command of the Ubuntu environment and ability to manage AWS instances via SSH.
- Experience working with relational databases and ability to assume administrative database responsibilities.
- Fluent in Python and experience interacting with data sources (web APIs, SFTP, S3 buckets, Airtable).
- Experience building scalable data pipelines using Airflow or similar orchestration frameworks.
- Proficiency with database concepts: primary keys, indexes, nullable fields, data types, partitioning, and data modeling.
- Prior experience handling sensitive data, including sensitivity classification, access controls, and audit logging; familiarity with employee data governance.
- Experience building data products, dashboards, or reporting tools using lightweight frontend frameworks such as Streamlit.
- Ability to analyze large datasets, identify gaps and inconsistencies, and communicate findings to non-technical stakeholders.
- Experience building data layers that support LLM-based tooling or agentic AI frameworks, including data quality, latency, and evaluation/feedback management.
- Proficiency using Git for version control and codebase management.
- Familiarity with system design principles applied to data platforms or AI-integrated systems.
- Solid understanding of data structures and algorithms for medium-complexity problems.
- Strong comfort working cross-functionally with technical and non-technical stakeholders.
Airbnb Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Airbnb and has not been reviewed or approved by Airbnb.
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Fair & Transparent Compensation — Pay ranges and total compensation components are increasingly disclosed, and country-level pay practices avoid location-based cuts, which feedback suggests improves consistency and perceived fairness.
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Healthcare Strength — Comprehensive core health coverage for employees, mental health resources, and substantial dependent support are repeatedly highlighted as robust and a standout element of the package.
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Leave & Time Off Breadth — Generous PTO, a winter shutdown, sabbaticals, and paid volunteer time are described as extensive, with parental leave and phased return options reinforcing time-off flexibility.
Airbnb Insights
What We Do
Airbnb is a community based on connection and belonging—a community that was born in 2008 when two hosts welcomed three guests to their San Francisco home, and has since grown to 4 million hosts who have welcomed over 800 million guest arrivals to about 100,000 cities in almost every country and region across the globe. Hosts on Airbnb are everyday people who share their worlds to provide guests with the feeling of connection and being at home. At Airbnb, we believe that hosts, guests and the communities where we operate are all stakeholders we have a responsibility to serve, and that by serving them alongside our employees and investors, we will build an enduringly successful company.
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