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The Experimentation team provides cutting edge tooling and methodologies for all teams at Uber to make rapid decisions for their product iterations. Experimentation is an exciting domain that combines multiple disciplines of Software Engineering (Backend, Distributed Systems, Mobile, Web, Data Infra), Data Science, and Product Design. Every major launch across any of Uber's Rides, Delivery, Earner, Freight, and Uber For Business (U4B) organizations leverages the Experimentation platform to determine how new features impact key business metrics. Virtually all Engineers, Scientists, and Product Managers at the company use our platform on a daily basis to launch, monitor, test, and make changes to Uber's ecosystem.
Job Responsibility:
Grow, mentor, and develop teams of skilled software engineers and engineering managers within Measurement & Optimizations org
Recruit high quality engineering talent for the team as needed
Establish relationships and collaborate with key stakeholders across Uber to further the team goals
Own the definition, execution, and delivery of KPIs for your teams
Uphold a high bar for engineering excellence and platform reliability
Define the processes and systems within the team to positively shape engineering culture
Help define the roadmap and vision for Experimentation
Requirements:
Bachelor's or Master's degree in Computer Science or a related technical field, or equivalent experience in an engineering related bootcamp
5+ years experience as an engineering manager
5+ years of experience as a software engineer or equivalent
Experience going through the full software cycle of requirements, design, coding / testing, rollout / deployment, and best practices in delivering world-class software and services
Experience evolving and presenting a strong vision/roadmap for your team
Passion about your team's mission and the self-starting personality to make things happen
A track record of building teams with a culture of craftsmanship and engineering excellence
A track record of delivering results even when requirements are under-specified
Strong grasp of distributed-systems fundamentals: caching, sharding, consensus, fault tolerance, observability, and incident response
Excellent written and verbal communication skills, including the ability to document system architectures and algorithms
Nice to have:
BS/MS/PhD degree in Computer Science, a related field, or equivalent experience
Experience building or using A/B testing or feature flagging infrastructure
Experience building engineering or analytics tools or data products
A background in applied statistics with experience building systems at the boundary between data science and engineering
Experience shipping high scale systems: 100,000+ QPS
Experience managing teams with diverse technical backgrounds like front-end, backend, mobile, and data engineering