As Airbnb grew, the company’s needs for data timeliness and quality and focus on cost and compliance increased. In response to these new expectations, the company defined a Data Quality Initiative to achieve 5 primary goals related to data ownership, pipelines, validation, documentation, and discoverability. In this blogpost, Jonathan Parks, Vaughn Quoss, and Paul Ellwood discuss how the company achieved these goals, including by hiring data engineers organized in distributed pods; creating communication channels like forums and working groups to streamline decision-making processes; redefining normalized data and subject area-based data models; implementing new data pipeline technologies (e.g. Spark, Scala, automated data quality and anomaly detection checks); and creating a certification process for trusted datasets.