招聘

Engineering Manager - Compute Infra
Mountain View, California; San Francisco, California
·
On-site
·
Full-time
·
2mo ago
薪酬
$190,000 - $253,750
福利待遇
•Equity
必备技能
Distributed Systems
Engineering Management
Team Leadership
P-931
At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.
At Databricks, the Compute Infrastructure organization builds and operates the foundation that runs all Data, AI and stateful workloads across all major clouds. Our platform launches tens of millions of VMs per day, operates thousands of Kubernetes clusters, and must deliver extreme elasticity, reliability and cost efficiency.
We are looking for an Engineering Manager to lead a team responsible for critical components of this platform. Your work will directly influence product velocity, customer experience, and the company’s ability to scale.
The impact you will have:
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Own and evolve the compute platform to support all Databricks workloads, enabling engineers to build world-class products with high velocity and best-in-class performance.
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Hire exceptional engineers and invest in their growth through coaching, feedback, and career development.
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Raise the technical and operational bar through strong design practices, testing, and a culture of engineering excellence and platform mindset.
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Partner with engineering and product leadership to define long-term strategy and roadmaps.
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Lead cross-team initiatives that span product and infrastructure surface areas.
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Influence architectural decisions beyond your immediate team.
What we look for:
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10+ years of experience building and operating large-scale distributed systems, including strong practices around testing, monitoring, and reliability.
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3+ years of engineering management experience leading high-performing teams.
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Deep expertise in cloud infrastructure (AWS, Azure, GCP) and containerized environments (Kubernetes) is preferred.
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Proven ability to collaborate across engineering, product, and business stakeholders.
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Experience scaling teams and systems through rapid growth.
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BS, MS, or PhD in Computer Science or related field, or equivalent experience.
Pay Range Transparency:
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Local Pay Range**$190,000—$253,750 USD**
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits:
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks.
Our Commitment to Diversity and Inclusion:
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
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关于Databricks

Databricks
Series IDatabricks, Inc. is an American software company based in San Francisco. It was founded in 2013 by the original creators of Apache Spark. It offers a cloud-based platform for data analytics and artificial intelligence.
6,000+
员工数
San Francisco
总部位置
$43B
企业估值
评价
3.8
10条评价
工作生活平衡
2.8
薪酬
4.0
企业文化
4.2
职业发展
3.5
管理层
4.0
72%
推荐给朋友
优点
Innovative technology and cutting-edge projects
Supportive and collaborative team environment
Good benefits and competitive compensation
缺点
Poor work-life balance and long hours
High pressure and stressful environment
Heavy workload and overtime requirements
薪资范围
34个数据点
Mid/L4
Senior/L5
Mid/L4 · Corporate Development Manager
1份报告
$171,004
年薪总额
基本工资
$148,699
股票
-
奖金
-
$171,004
$171,004
面试经验
6次面试
难度
3.2
/ 5
时长
21-35周
体验
正面 0%
中性 83%
负面 17%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Coding Round
5
Onsite/Virtual Interviews
6
Offer
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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