Staff Analytics Engineer, Trust

airbnb, Inc.; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

Airbnb is seeking a Staff Analytics Engineer to join their Trust organization. This role involves developing foundational data sets, collaborating with various teams, and influencing data quality to ensure a secure environment for hosts and guests. Candidates should have extensive experience in analytics engineering and substantial technical skills, particularly in SQL and data engineering languages.

Benefits

Bonus potential

Equity options

Benefits package

Employee Travel Credits

Qualifications

• 9+ years of experience in Analytics Engineering, Data Science, or Data Engineering.
• Proven expertise in SQL and at least one programming language for data engineering.
• Extensive experience with data warehousing and modeling.

Responsibilities

• Architect and develop high-quality data assets for analytics and product use cases.
• Collaborate with cross-functional teams to align on data requirements and deliverables.
• Champion data quality improvements to enhance decision-making processes.

Skills

SQL

Python

Scala

Data Visualization

Data Warehousing

Problem-solving

Tools

Tableau

Airflow

PostgreSQL

MySQL

Redshift

BigQuery

ClickHouse

Job description

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Community You Will Join:

Everyone at Airbnb thinks about trust, but our team obsesses over it daily. The Trust organization is responsible for protecting our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards.

The Difference You Will Make:

As a Staff Analytics Engineer, you will work in a team of engineers with diverse expertise to build foundational data sets that power insights for the company and our host community. You will be operating with a high level of autonomy, collaborating directly with product, business partners, and peer engineering teams to align on requirements and execute effectively. You will review the designs and work of engineers on the team, and set a high bar for quality. You will also work closely with data scientists and economists to identify data sources and structure for foundational data sets.

A Typical Day:

• Architect and develop high quality data assets for product and analytics use cases, as well as for sharing with external partners
• Collaborate and build relationships with partners including backend/client, data science, analytics, and ML
• Develop frameworks, tools, and dashboards to scale insight generation to meet critical business, product, and regulatory requirements
• Translate ambiguously expressed data requirements into efficient, scalable, and impactful deliverables.
• Present product and technical deep dives to key stakeholders
• Influence the trajectory of data in decision making
• Improve trust in our data by championing for data quality across the stack

Your Expertise:

• 9+ years of experience experience in Analytics Engineering, Data Science, Data Engineering, or similar field
• Expertise in SQL and proficiency in at least one data engineering language, such as Python or Scala
• An ability to navigate metric and data considerations in the Trust domain, including uncertain risk assessment and late-landing signals.
• Expertise creating metrics, evaluating effectiveness of defenses - ex: rules and ML models utilizing evaluation and experiment data.
• Experience with Tableau and data visualization tools generally
• Experience with an ETL framework like Airflow
• Excellent communication skills with a history of strong collaborations with technical and non-technical partners
• Expertise with data warehousing and modeling. Hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse)
• Strong problem-solving skills and the ability to troubleshoot complex data issues

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.