Staff Software Engineer - Revenue Intelligence (Remote)

Cloudbeds

Zürich

Vor Ort

CHF 121.000 - 169.000

Vollzeit

Vor 6 Tagen
Sei unter den ersten Bewerbenden

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Benefits dieser Stelle

Remote work worldwide
Home office stipend based on residency
Fully Paid Parental Leave
Wellness Fridays

Zusammenfassung

Cloudbeds is seeking a Staff Software Engineer for Revenue Intelligence. You will shape architecture and drive delivery across customer-facing apps, backend services, data pipelines, and ML workflows in a completely remote European setup.

You will lead modernization while ensuring reliability, security, and scalable growth, mentoring teams and aligning multiple groups around durable technical decisions.

Qualifikationen

  • 10+ years of software engineering experience with leadership across complex systems.
  • Strong hands-on expertise in Python and distributed architectures.
  • Experience with data-intensive systems and modern cloud tooling.
  • Proven ability to guide cross-functional teams and drive architectural decisions.

Aufgaben

  • Set and evolve technical strategy for Revenue Intelligence platforms.
  • Lead design and delivery of features across web apps, APIs, data pipelines, and ML workflows.
  • Identify and mitigate scalability, reliability, security, and observability risks.
  • Modernize legacy systems with incremental, production-friendly migrations.
  • Mentor teams and raise engineering standards through documentation and guidance.

Kenntnisse

Python
Distributed systems
Cloud engineering
Kubernetes
Terraform
Leadership
Communication
Observability
Security best practices
Data processing

Tools

PostgreSQL
Redshift
APIs design
CI/CD tooling

Jobbeschreibung

Cloudbeds is seeking a Staff Software Engineer for Revenue Intelligence. You will shape architecture and drive delivery across customer-facing apps, backend services, data pipelines, and ML workflows in a completely remote European setup.

You will lead modernization while ensuring reliability, security, and scalable growth, mentoring teams and aligning multiple groups around durable technical decisions.

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