Senior Data Engineering, Payments

Airbnb

Posted 23d ago

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Design, build, and maintain robust, scalable data pipelines that ingest, reconcile, transform, and publish data for AirCover products and operations.
Develop high-quality, analytics-ready data models and metrics that support executive reporting, claims and operations workflows, experimentation, financial reconciliation, and self-serve analysis.
Partner with software engineers and external-data stakeholders to translate source-system behavior and partner data feeds into trustworthy offline datasets.
Ensure data quality, consistency, accuracy, and documentation across critical AirCover data assets.
Improve the reliability, maintainability, and observability of pipelines through strong testing, monitoring, and engineering standards.
Collaborate cross-functionally with Product, Engineering, Operations, Finance, Analytics, and Data Science to define data requirements and deliver solutions that drive business outcomes.
Contribute to the broader Data Engineering community at Airbnb by influencing tooling, standards, and best practices.
Help raise the bar for foundational data systems that can scale with new AirCover markets, products, and regulatory or partner requirements.

6+ years of relevant industry experience in data engineering, software engineering, or closely related fields.
Strong experience designing and maintaining production-quality ETL or ELT pipelines.
Strong data modeling skills, including experience structuring data for business-relevant analytics and operational use cases.
Hands-on experience with large-scale distributed data processing technologies such as Spark and distributed storage systems.
Strong SQL skills and proficiency in at least one programming language commonly used in data engineering, such as Python, Scala, or Java.
Experience with workflow orchestration or ETL scheduling frameworks such as Airflow.
Experience working with structured and third-party data sources, including reconciliation and transformation into trustworthy warehouse models.
Excellent written and verbal communication skills, with the ability to work effectively across technical and non-technical stakeholders.
Sound judgment around data quality, documentation, ownership, and long-term maintainability.

Experience supporting insurance, risk, trust, compliance, or financial data domains.
Experience working with external partner data feeds, reconciliations, or operational reporting systems.
Familiarity with experimentation data, executive metrics, or business performance dashboards.
Experience improving data quality frameworks, observability, or automated testing for critical data assets.
Experience building foundational datasets used across multiple teams and use cases.

Skills