Staff Data Engineer, Communication & Connectivity

Nubeero Limited; Northern (KY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Airbnb is seeking a senior data engineer to lead the design and build of large-scale, distributed data systems powering ML products and features across the Messaging & Connectivity domain.

The role focuses on shaping the long-term data architecture, collaborating with backend, client, data science, and analytics teams, and delivering reliable data pipelines in both batch and real-time modes.

Qualifications

• 9+ years of relevant industry experience or 6+ years with a PhD in CS/EE or related field.
• Bachelor's or Master's in CS/EE or equivalent experience; PhD is a plus.
• Strong CS fundamentals and familiarity with architecture patterns.
• Experience running production data pipelines with Spark or Flink.
• Experience collaborating across client, backend, ML, analytics teams.
• Ability to define and guide overarching data architecture across teams.

Responsibilities

• Shape the team’s long-term vision and roadmap in collaboration with cross-functional partners.
• Build relationships with partner engineering teams to drive impactful outcomes.
• Design, build, and maintain scalable data pipelines (batch and real-time).
• Implement offline/online feature building to speed ML product delivery.
• Architect ML infra, optimize for performance, scalability, and cost.
• Mentor engineers and influence the data engineering community.

Skills

Cross-functional collaboration

Distributed data processing

Data architecture

Product-focused mindset

Strong CS fundamentals

Education

Bachelor's or Master’s in CS/EE

PhD

Tools

Apache Spark

Flink

Job description

Airbnb is seeking a senior data engineer to lead the design and build of large-scale, distributed data systems powering ML products and features across the Messaging & Connectivity domain.

The role focuses on shaping the long-term data architecture, collaborating with backend, client, data science, and analytics teams, and delivering reliable data pipelines in both batch and real-time modes.