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Staff Engineer – Usage Based Billing

Staff Engineer – Usage Based Billing

CompanyStripe
LocationUnited States
Salary$Not Provided – $Not Provided
TypeFull-Time
Degrees
Experience LevelSenior, Expert or higher

Requirements

  • 8+ years of experience in full time software development roles.
  • Extensive experience working in complex distributed systems with significant scale and reliability requirements.
  • Proficiency in at least one modern programming language (e.g. Java, Ruby, Python).
  • Experience with big data technologies (e.g. Flink, Kafka, Pinot, Iceberg) and a solid understanding of data modeling and database systems.
  • Self-directed and can operate autonomously across multiple teams to deliver scaled impact.
  • Experience as a technical lead, including defining the roadmap for complex projects spanning multiple teams and functions.
  • Experience mentoring and growing senior engineers.

Responsibilities

  • Lead by example in designing, building, and operating scalable and reliable usage-based billing functionality.
  • Drive architecture and technical breakdown discussions, both within and across teams.
  • Partner closely with engineering and product leadership to define our technical strategy.
  • Make effective tradeoffs that consider business priorities, user experience, and a sustainable technical foundation.
  • Develop and lead execution against both short-term and long-term roadmaps.
  • Identify and prioritize investments to continuously improve reliability and performance.
  • Work closely with platform teams across Stripe to align on technical dependencies and unblock long-term roadmap delivery.
  • Work in a variety of languages and technologies, including Java, Ruby, Kafka, Flink, and Pinot.
  • Mentor and coach individual contributors to become the next generation of leaders at Stripe.

Preferred Qualifications

  • Experience with building and operating high scale, real-time data processing systems using technologies like time series databases and Flink.
  • Experience evaluating and optimizing data storage solutions to balance long-term trade offs between cost and performance.