Руководящая инженерная роль в крупной компании в сфере данных: понятная зона ответственности за высоконагруженную платформу и зарплата выше рыночного ориентира. При этом нужно работать в гибридном формате в Белвью.
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Текст:
Hirify AI/Оригинал
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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