Analytics Engineer

Summary

Join Airbnb's Trust organization as a Staff Analytics Engineer and build foundational data sets that power insights for the company and its host community. Collaborate with various teams, including product, business partners, and peer engineering teams, to align on requirements and execute effectively. You will review the work of other engineers, setting a high bar for quality, and work closely with data scientists and economists. A typical day involves architecting and developing high-quality data assets, collaborating with partners, developing frameworks and dashboards, translating data requirements into deliverables, presenting to stakeholders, and improving data quality. This role requires 9+ years of experience in a relevant field and expertise in SQL, Python or Scala, data visualization, ETL frameworks, data warehousing, and relational and columnar databases. The position is US-remote eligible with occasional office work.

Requirements

• 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

Responsibilities

• 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

Benefits

• Bonus
• Equity
• Benefits
• Employee Travel Credits