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高级软件工程师 - 后端

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查看雇主原标题Senior Software Engineer - Backend

Databricks · Vancouver, 加拿大

职位信息来自雇主公开的招聘页面。申请前请务必在雇主官网核实详情。

为什么值得关注?

发现指数 42/100,仅依据与该职位一起存储的证据计算。

42/100 发现指数
  • 新的雇主官方职位

分数构成

  • 时效性 (随职位发布时间变化)+18
  • 雇主官方来源+15
  • 稀有职位+1
  • 公司来源健康度+8

该职位未包含:已披露薪资、远程职位、提及签证担保、提及搬迁、未出现在监控的职位板上。

这些理由来自雇主自己的职位描述与我们核实过的来源检查结果。除了已存储的信号之外,我们不做任何推测。

职位描述

机器翻译

P-1440

Databricks 的使命是简化和普及数据与 AI —— 从让下一代交通方式成为现实,到加速医学突破的研发。我们通过构建和运营全球最顶尖的数据与 AI 基础设施平台来实现这一目标,让客户能够利用深度数据洞察来改进其业务。我们由工程师创立 —— 并且痴迷于客户 —— 我们抓住每一个机会解决技术挑战,从设计用于与数据交互的下一代 UI/UX,到在数百万台虚拟机上扩展我们的服务和基础设施。而我们才刚刚开始。

温哥华将成为 Databricks 最新的研发中心,扩大我们在太平洋西北地区的布局。我们正在积极招聘世界一流的工程师,加入我们普及数据 + AI 的使命。

我们设想温哥华站点将成为 Databricks 产品创新的关键驱动力。首先,我们将把几个战略领域带到温哥华站点,我们在以下团队中有多个开放职位,包括:

• 日志分析 - 我们的客户越来越多地使用 Databricks 实时分析 PB 级日志。这在整个数据处理管道中带来了新的挑战,包括数据摄取、索引、处理以及用户体验本身。

• AI/BI - AI/BI 正在重新定义 AI 时代的商业智能。我们在去年夏天推出了这款产品,并且已经看到了巨大的采用率(我们 98.7% 的数据仓库客户已经在使用 AI/BI!)。从丰富的仪表板构建和高级可视化,到强大的对话式数据分析解决方案,我们正在构建的产品涉及整个技术栈中令人兴奋的技术挑战。

• Unity Catalog Business Semantics - 上下文对 AI 来说就是一切。对于企业数据,这些上下文需要被治理和管理,而这正是 Unity Catalog Business Semantics 所提供的。我们在上一次 Data + AI Summit 上刚刚推出了首个语义建模能力 Unity Catalog Metrics,但我们还有更多储备。该团队的工程师工作在大规模分布式系统、数据建模、治理和 AI 赋能交汇的领域。

• Databricks Apps - Databricks Apps 是 Databricks 增长最快的产品之一,已有超过 2,500 家客户使用,他们创建了超过 20,000 个应用 —— 而它直到去年六月才正式 GA。Apps 团队是少数能够接触底层平台组件(k8s、网络)的团队之一,拥有核心技术(应用运行时和代理),并在大力投资应用构建器 AI 智能体。

我们看重什么:

• 计算机科学、相关技术领域学士(或更高)学位,或同等实践经验。

• 能够适应在多年愿景下工作,并以增量交付推进。

• 以交付客户价值和影响力为动力。

• 5 年以上 Java、Scala 或 C++ 的生产级经验。

• 在算法和数据结构及其实际应用场景方面有扎实基础。

任职要求

• 有在 SaaS 平台或面向服务架构(SOA)上工作的经验。

• 有云技术经验,例如 AWS、Azure、GCP、Docker 或 Kubernetes。

• 有处理敏感数据的安全和系统方面的经验。

• 良好的 SQL 知识。

福利待遇

在 Databricks,我们致力于提供全面的福利和津贴,以满足所有员工的需求。有关您所在地区所提供福利的具体详情,请点击此处。

我们对多元与包容的承诺

在 Databricks,我们致力于营造多元和包容的文化,让每个人都能脱颖而出。我们非常重视确保我们的招聘实践具有包容性,并符合平等就业机会标准。申请 Databricks 职位的人士不会因年龄、肤色、残疾、族裔、家庭或婚姻状况、性别认同或表达、语言、国籍、身体和心理能力、政治派别、种族、宗教、性取向、社会经济状况、退伍军人身份以及其他受保护特征而受到区别对待。

合规

如果履行工作职责需要接触受出口管制的技术或源代码,雇主可自行决定是否为此类职位申请美国政府许可证,并且雇主可能仅基于这一原因而拒绝继续推进某位申请人。

薪资

Databricks 致力于公平和公正的薪酬实践。该职位的薪酬范围列于下方,代表非佣金制职位的预期薪资范围,或佣金制职位的目标收入。实际薪酬方案取决于每位候选人独有的多个因素,包括但不限于与工作相关的技能、经验深度、相关认证和培训,以及具体工作地点。基于上述因素,Databricks 预计将使用该范围的完整宽度。该职位的总薪酬方案还可能包括年度绩效奖金、股权以及上述福利的资格。

加拿大薪酬范围 $146,200 — $201,100 CAD

关于 Databricks

Databricks 是一家数据与 AI 公司。全球超过 20,000 家组织 —— 包括 adidas、AT&T、Bayer、Block、Mastercard、Rivian、Unilever,以及 70% 的《财富》500 强企业 —— 依赖 Databricks Data + AI Platform 来构建和扩展数据与 AI 应用、分析和智能体。Databricks 总部位于旧金山,在全球拥有 30 多个办事处,提供统一平台,包括 Genie、Lakebase、Agent Bricks、Lakeflow、Lakehouse 和 Unity Catalog。如需了解更多信息,请在 LinkedIn、X、YouTube 和 Instagram 上关注 Databricks。

以上内容由机器翻译自动生成,可能存在错误;投递前请以雇主原文为准。

查看雇主原文

职位描述

P-1440

Databricks is on a mission to simplify and democratize data and AI — 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.

Vancouver will be the newest R&D center for Databricks, expanding our presence in the Pacific Northwest. We are actively hiring world-class engineers to join us on our mission to democratize data + AI.

We envision the Vancouver site becoming a key driver of product innovation at Databricks. To start, we’re bringing a few strategic areas to the Vancouver site and we have several open roles across the teams below, including:

• Log Analytics - Our customers increasingly use Databricks to analyze petabyte-scale logs in real time. This creates new challenges across the entire data processing pipeline, including ingestion, indexing, processing, and the user experience itself.

• AI/BI - AI/BI is redefining Business Intelligence for the AI age. We launched this product last summer and have already seen tremendous adoption (98.7% of our data warehousing customers are already using AI/BI!). From rich dashboarding and advanced visualizations to powerful talk-to-your-data solutions, the products we are building involve exciting technical challenges across the entire stack.

• Unity Catalog Business Semantics - Context is everything for AI. For enterprise data, that context needs to be governed and managed, which is what Unity Catalog Business Semantics offers. We recently launched our first Semantics modelling capability, Unity Catalog Metrics, this past Data + AI Summit but we have a lot more in store. Engineers on this team work at the intersection of large scale distributed systems, data modeling, governance, and AI enablement.

• Databricks Apps - Databricks Apps is one of the fastest growing products at Databricks, used by more than 2,500 customers who have created more than 20,000 apps — and it was only GA’ed this past June. The Apps team is one of the few teams that are exposed to low-level platform components (k8s, networking), owns fundamental tech (apps runtime and proxy), and is heavily investing in app builder AI agents.

What we look for:

• BS (or higher) in Computer Science, related technical field or equivalent practical experience.

• Comfortable working towards a multi-year vision with incremental deliverables.

• Motivated by delivering customer value and impact.

• 5+ years of production level experience in either Java, Scala or C++.

• Strong foundation in algorithms and data structures and their real-world use cases.

任职要求

• Experience working on a SaaS platform or with Service-Oriented Architectures.

• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, or Kubernetes.

• Experience with security and systems that handle sensitive data.

• Good knowledge of SQL.

福利待遇

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 click here .

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.

薪资

Databricks is committed to fair and equitable compensation practices. The pay range 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 anticpates 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.

Canada Pay Range $146,200 — $201,100 CAD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram .

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