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Lead Engineer – Atlas Stream Processing

Lead Engineer – Atlas Stream Processing

CompanyMongoDB
LocationSan Francisco, CA, USA
Salary$137000 – $270000
TypeFull-Time
Degrees
Experience LevelSenior, Expert or higher

Requirements

  • 5+ years of experience of building distributed systems, and/or foundational cloud services at scale and experience with a compiled language (Java, C#, Go, etc.)
  • 2+ years of experience managing a team of 3+ engineers and providing technical leadership
  • Track record in hiring, mentoring, and growing high-performing software engineering teams, experience working with remote teams and a passion for mentoring and career development of the team
  • Excellent verbal and written technical communication skills and desire to collaborate with colleagues, other teams, and lead projects
  • Strong background in building core components for data processing systems (including query execution, storage engines, autotuning and workload optimization) and distributed systems
  • Have led the launch of new features and maintained them in production

Responsibilities

  • Manage a team of software engineers, responsible for ensuring their success, aiding their career growth, and facilitating their technical work
  • Make coding contributions to the team’s projects
  • Work with product managers, program managers, design & analytics teams and other teams to define, prioritize and deliver new features that delight our users and drive platform improvements
  • Take responsibility for the planning and execution of major features, raise delivery risks
  • Own the monitoring, operations, and maintenance of the systems your team develops
  • Enable the team to operate efficiently by removing technical obstacles, coordinating with other teams on dependencies, and prioritizing the team’s overall well-being
  • Contribute to planning for organizational growth, including allocation of engineering resources, participate in hiring and assignment of projects

Preferred Qualifications

  • Bonus points for experience with containerization and orchestration platforms (eg. Kubernetes) and observability tools