Principal Engineer, Cloud Data Infrastructure

Increases results & effectiveness of all software engineers in a large domain Sets the technology roadmap for a domain Adapts their role to the need, selecting the most effective means of realizing their technical goals Exercises wide latitude in determining objectives and approaches to assignments and takes initiative to achieve results Handles ambiguous and unfamiliar situations and uses creativity to deliver decisive resolutions Uses discovery & exploratory research, not being limited to technical domains, to make successful decisions Identifies themes & trends that span projects and teams, and finds broadly impactful opportunities for improvement Uses professional savvy to determine when industry-standard solutions can be adopted, versus when a problem space warrants a novel solution (“build/buy”) Mentor others as a means of propagating technical influence, and to enhance the performance of their organization 10+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. 15+ years of professional experience in software engineering or data platform roles, with a bachelor's degree in computer science, engineering, or equivalent practical experience. 5+ years building and operating large-scale distributed systems in production cloud environments (AWS preferred). Deep, hands-on technical expertise across data and messaging systems — relational and NoSQL databases, distributed caching, and message queue architectures; you can get into the internals when needed. Strong DevOps engineering background including infrastructure as code, CI/CD for data systems, and automation-first operational practices. Demonstrated experience with AI-first development practices and the ability to apply AI tooling to accelerate engineering productivity. Demonstrated track record delivering performance improvements and scalability enhancements for consumer-facing applications serving tens of millions of users. Established record of technical influence across large engineering organizations without direct management authority. Strong written and verbal communication skills, including the ability to present complex technical trade-offs to executive stakeholders. Background in financial technology, payments processing, or regulated industries. Experience supporting transaction processing systems requiring extreme reliability and millisecond-level response times. Familiarity with resilience engineering, failure injection testing, and business continuity planning. Knowledge of modern data pipeline frameworks and real-time analytics architectures. History of mentoring and growing senior/staff-level engineers into technical leadership roles. Experience integrating AI/ML workflows into data platform infrastructure including vector databases, feature stores, or LLM serving infrastructure.