Назад
9 дней назад

Software Engineering Manager (Snowpark)

236 000 - 339 200$
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Software Engineering Manager (Snowpark): Building and scaling a cloud-native compute platform for AI, ML, data science, and data engineering workloads with an accent on distributed systems, serverless computing, and high-performance infrastructure. Focus on defining technical strategy, leading complex cross-functional projects, improving reliability and service health, and mentoring engineers.

Location: Bellevue, Washington, United States; hybrid

Salary: $236K–$339.2K annually

Company

Snowflake provides a cloud data platform that enables enterprises to run large-scale data workloads with elastic performance and concurrency.

What you will do

  • Provide technical and strategic direction for the Snowpark compute platform, including its technology ecosystem, roadmap, and vision.
  • Plan and lead complex technical projects involving multiple teams across the company.
  • Influence technical direction, product investment, team priorities, and strategic pivots.
  • Improve team productivity through tools, processes, and engineering solutions.
  • Strengthen product stability, reliability, service health, on-call operations, customer support, diagnosability, and manageability.
  • Build team expertise by identifying skill gaps, mentoring engineers, and developing technical talent.

Requirements

  • 8+ years of industry experience designing and building large-scale distributed systems platforms.
  • 2+ years of full-time software engineering management experience.
  • Experience with cloud-native architectures and serverless compute platforms.
  • Strong interest in improving developer productivity and supporting engineers’ career growth.
  • Ability to work in a hybrid setup in Bellevue, Washington, United States.
  • Ability to follow confidentiality and data security standards for handling sensitive customer information.

Culture & Benefits

  • AI-native, experimental approach to solving problems and improving how work gets done.
  • Low-ego environment focused on innovation, fast execution, and challenging conventional thinking.
  • Opportunity to work on a high-scale compute platform supporting AI, ML, data science, and data engineering workloads.
  • Confidentiality and customer data security are core responsibilities for every employee.

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