Data Science & Data Platform Engineering

This blog aims to introduce Airbnb’s experience upgrading Data Warehouse infrastructure to Spark and Iceberg

How we redesigned payments data read flow to optimize client integrations, while achieving up to 150x performance gains.

Airbnb’s VP of Engineering on why you don’t have to change your natural self to be a leader

by: Jimmy O’Neill

Part three of a series on how we provide powerful, automated, and scalable data privacy and security engineering capabilities at Airbnb

Part two of a series on how we provide powerful, automated, and scalable data privacy and security engineering capabilities at Airbnb

Learn more about how to migrate your Kafka cluster from one Zookeeper cluster to another without any user impact.

Consolidating long-running, lightweight tasks for improved resource utilization

Part-III: Building a coherent consumption experience

Part one of a series on how we provide powerful, automated, and scalable data privacy and security engineering capabilities at Airbnb.

Gaining trust in data with extensive data quality, accuracy and anomaly checks

The propensity score matching model powering how we optimize for long-term decision-making

Part II: The six design principles of Minerva compute infrastructure

How Airbnb built a unified tracking measurement system to support marketing campaigns

Part-I: Introducing Minerva — Airbnb’s Metric Platform

The path to cloud efficiency begins with a cost data foundation

by Chris Williams, Ken Chen, Krist Wongsuphasawat, and Sylvia Tomiyama

How Airbnb customized Superset for business intelligence at scale

Introducing the Airbnb Experiment Guardrails framework, which helps us prevent negative impact on key metrics while experimenting at scale.

Part 2 — A New Gold Standard

Part 1 — Rebuilding at Scale

Part one of a series on how we will measure discrepancies in Airbnb guest acceptance rates using anonymized perceived demographic data.

One of the most common ways to store results from a Spark job is by writing the results to a Hive table stored on HDFS. While in theory…

There is often a hidden performance cost tied to the complexity of data pipelines — Overhead. In this post we will examine the concept of…