Tech Stack

Description

You will lead a team of data engineers to build scalable data foundations for Airbnb's Communication & Connectivity organization, enabling intelligent features across Notifications, Messaging, Hosting Services, and Partner Ecosystem. Collaborate closely with ML, product, and analytics teams to architect data pipelines, govern key metrics, and deliver high-quality data that powers personalized, timely communications for hosts and guests.

Requirements

• 9+ years of industry experience with a focus on data engineering and analytics engineering.
• 4+ years of experience managing and leading data engineering teams with proven ability to mentor and grow engineering talent.
• Proficiency in data processing technologies (batch and streaming), SQL, and ETL schedulers (e.g., Airflow, Dagster).
• Demonstrated ability to drive complex cross-team data engineering projects, specifically enabling Machine Learning features and collaborating with ML/AI teams.
• Experience in designing, building, and governing key business metrics across a diverse product portfolio.
• Strong technical and strategic vision with ability to translate broad objectives into actionable engineering plans.
• Strong product and business sense; can spot potential data issues, provide alternative solutions, and collaborate effectively with partners.
• Excellent communication skills with ability to interact with technical and non-technical stakeholders.
• Passion for innovation and fostering a culture of learning and continuous improvement.

Responsibilities

• Lead and manage a team driving data engineering projects across Notifications, Messaging, Hosting Services, and the Partner Ecosystem.
• Collaborate with the ML team to design and deliver robust data foundations (batch, intraday, streaming) enabling new product features and AI/ML models.
• Drive development of key metrics across the C&C org, partnering with Analytics and Product to define, build, and govern metrics that measure business impact and product health.
• Collaborate with Product, Analytics, ML, and Engineering to define and prioritize impactful data initiatives.
• Streamline team practices ensuring effective prioritization, execution, and clear communication of roadmap commitments.
• Advocate for best engineering practices including testing, monitoring, and continuous improvement.
• Assess system health and data quality, identifying key areas for investment and scalability.
• Mentor and develop engineers, fostering an inclusive and high-performing team culture.
• Align team priorities with organizational goals, partnering with senior leadership.