Senior Data Engineer, People Analytics
Airbnb
| Company | Airbnb |
| Category | Engineering |
| Location | United States |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 8 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
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 p
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