Data Engineer, Trust

Job Description

What is Trust at Airbnb

Over two million people stay on Airbnb every night and the Trust Engineering team keeps our hosts and guests safe and supported throughout the entire Airbnb experience.

As part of the Trust Engineering team you will be in charge of designing and building scalable and robust systems to detect and mitigate fraud across our entire platform. You will be deeply involved in the technical details of building highly available and real-time risk detection services in close collaboration with product, data science and operations teams to understand ever evolving attack vectors and to make Airbnb the world’s most trusting community.

What is Data Engineer on Trust at Airbnb

On Trust our vision is to build the world’s most trusting community, data is at the center of that goal. As a Data Engineer on Trust, you’ll play a critical role in helping keep Airbnb’s businesses and our community safe from account takeovers, objectionable content, fraudulent transactions, hate speech, spam and other kinds of fraud and abuse.

We’re looking for strong data engineers to uplevel our data foundation which powers reporting, analysis and ML modeling across Trust. The work includes developing and automating large scale, high performance data processing systems, data modeling and improving our existing data model for better efficiency and quality, and partnering closely with all stakeholders to create the technology that generates and transforms data into applications, insights and experiences towards our vision.

Projects:

• We created a multi-tiered system of user verifications to protect Airbnb user accounts, including defenses such as SMS code and email verification, micro-authorization challenges, 3-D Secure, and more.
• The team built the data pipeline to ingest rich chargeback data from an array of payment processors in a robust and scalable manner, payin and payout anomaly detection systems which analyze hundreds of thousands transactions every day.
• The team built the high-throughput low-latency framework to intercept all platform requests for risk evaluation purposes, check user capability restrictions and apply remediation actions to mitigate risk.
• We've built the rules engine system similar to Facebook's Haxl which is highly optimized for efficient fetching and batching of large amounts of data that powers all our machine learning models.

Minimum Qualifications/Requirements

• 4+ years of relevant industry experience in Data Engineering working with large scale data driven system.
• Strong knowledge of relational databases and query authoring (SQL)
• Experience with ETL design, implementation, maintenance and familiar with at least one data pipeline framework like Airflow
• Experience and working knowledge with Big Data frameworks like Hive, Spark, Presto, Hadoop, MapReduce, etc.
• Proficient in at least one programming language for data engineering (e.g. Java/Scala/Python)
• Experience designing and deploying high performance data processing systems with reliable data validation, monitoring and logging practices
• Rigor in high code quality, automated testing, and other engineering best practices.
• Outstanding communication and interpersonal skills and detail oriented
• Bachelor’s and/or Master’s degree, preferably in CS, or equivalent experience

Preferred Qualifications

• Experience in fraud/spam detection and/or payment domain is a huge plus, but not required
• Experience with NoSQL databases such as HBase or Cassandra
• Familiarity with experimentation and machine learning techniques

Benefits:

• Stock
• Competitive salaries
• Quarterly employee travel coupon
• Paid time off
• Medical, dental, & vision insurance
• Life insurance and disability benefits
• Fitness discounts
• 401K
• Flexible Spending Accounts
• Apple equipment
• Commuter subsidies
• Community involvement (4 hours per month to give back to the community)
• Company sponsored tech talks and happy hours
• Breakfast, lunch, and dinner
• Much more...

Airbnb has Engineering offices along the West Coast in the U.S. and our teams are growing quickly! Contact us to find out which office works best for you.

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