Senior Data Engineer, People Analytics

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $179k - $210k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Airbnb

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2007

👥 B2C

🛍️ eCommerce

💰 Post-IPO Equity on 2020-12

B2C • eCommerce • Hospitality

Airbnb is a global online marketplace that connects people looking for accommodation with hosts offering unique and diverse lodging options, often in residential properties. Users can book spaces ranging from one-bedroom apartments to entire homes and boutique hotels. Airbnb also offers experiences, allowing guests to book activities hosted by locals, providing an authentic travel experience.

📋 Description

• 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

🎯 Requirements

• 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.

🏖️ Benefits

• 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.