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解决方案架构师 - 新兴企业(初创公司)

机器翻译
查看雇主原标题Solutions Architect - Emerging Enterprise (Startups)

Databricks · 美国

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 46/100,仅依据与该职位一起存储的证据计算。

46/100 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+5
  • 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-345

在Databricks,我们的客户向我们提出挑战,要求解决一些世界上最棘手的数据问题。我们的客户依赖我们的解决方案架构师团队来理解支撑我们平台的技术、更广泛的云和技术生态系统,以及如何将它们整合在一起来解决这些问题。

Databricks的解决方案架构师主导Databricks统一分析平台的采用。作为我们团队的一员,您将在Apache Spark™、MLflow和Delta Lake等开源项目上磨练技能,以在公有云提供商上倡导Lakehouse范式。您将获得云平台、数据工程、数据分析、数据科学和机器学习方面的专业知识。在这个面向客户的角色中,您将识别Databricks的用例,使用我们的平台开发架构和解决方案,并指导客户完成实施,以交付战略业务价值。您将与我们的客户建立关系,并确立自己作为值得信赖的顾问的地位。

Databricks的文化以协作和团队合作蓬勃发展,您将通过参与我们的主题专家小组,为我们的团队贡献您的知识。在这个角色中,您将向支持特定业务部门的解决方案架构师负责人汇报。

如果您是一位对数据和AI感兴趣的技术专家,并且喜欢为客户制作解决方案原型,那么这个角色适合您。

您将产生的影响:

• 为客户提供技术领导,以评估和采用Databricks的数据和AI解决方案

• 就大数据架构提供咨询,为战略客户项目、数据科学和机器学习项目实施概念验证,并验证与云服务和其他第三方应用程序的集成

• 为客户构建并展示参考架构、技术指南和演示应用程序

• 为关键的客户运营问题提供升级支持

• 成为Databricks驱动的开源项目(Apache Spark™、Delta Lake、MLflow、Koalas)的专家,并通过聚会、会议和网络研讨会,在开发者社区中传播这些项目

• 发挥您的优势帮助其他SA,并推动公司内部的跨职能关系

• 出差拜访客户(最高30%,其中80%以上在您所在地区本地)

我们寻找的是:

解决方案架构师是面向客户的。您需要能够通过演示、白板讨论、架构讨论和平台演示,自如地向各种受众传达想法。

• 5年以上面向客户的售前、技术架构或咨询角色经验

任职要求

• 能够使用Python、Scala、Java、SQL或R中的至少一种进行编程和调试

• 曾使用公有云提供商(如AWS、Azure或GCP)构建解决方案

• 数据工程技术(例如Spark、Hadoop、Kafka)

• 数据仓库(例如SQL、OLTP/OLAP/DSS)

• 数据科学和机器学习技术(例如pandas、scikit-learn、HPO)

• [优先] 定量学科(例如计算机科学、应用数学、运筹学等)学位

• 加分项:Databricks认证

福利待遇

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

我们对多元化和包容性的承诺

在Databricks,我们致力于培育一种多元化和包容性的文化,让每个人都能脱颖而出。我们非常谨慎地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。在Databricks寻求就业的个人,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、社会经济地位、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访问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,雇主也可能仅以此为由拒绝继续处理申请人的申请。

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。实际薪酬方案基于每位候选人独有的若干因素,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。有关您所在地区属于哪个范围的更多信息,请访问我们的页面此处。

本地薪酬范围 $139,700 — $247,300 USD

关于Databricks

Databricks是数据和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——依赖Databricks Data + AI Platform来构建和扩展数据与AI应用、分析和代理。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-345

At Databricks, our customers challenge us with solving some of the world's toughest data problems. Our customers rely on our Solutions Architect team to understand the technologies that power our platform, the broader cloud and technology ecosystems, and how they can all be brought together to solve these problems.

Solutions Architects at Databricks lead the adoption of the Databricks Unified Analytics Platform. As a member of our team, you will sharpen your skills on open-source projects such as Apache Spark™, MLflow, and Delta Lake to advocate the Lakehouse paradigm on public cloud providers. You will gain expertise in cloud platforms, data engineering, data analytics, data science, and machine learning. In this customer-facing role, you will identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through implementations to deliver strategic business value. You will build relationships with our customers and establish yourself as a trusted advisor.

Databricks' culture thrives on collaboration and teamwork, and you will contribute your knowledge to our teams by participating in our subject matter expert groups. In this role, you will report to the Solutions Architect Leader supporting the specific business segment.

If you are a technologist interested in Data and AI, and enjoy prototyping solutions for customers, this role is for you.

The impact you will have:

• Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks

• Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications

• Build and present reference architectures, technical guides, and demo applications for customers

• Provide escalated support for critical customer operational issues

• Become an expert in, and evangelize Databricks driven open-source projects (Apache Spark™, Delta Lake, MLflow, Koalas) across developer communities through meetups, conferences, and webinars

• Use your strengths to help your fellow SA's, and drive cross-functional relationships across the company

• Travel to customers (up to 30%, of which 80%+ local to your region)

What we look for:

Solution Architects are customer-facing. You'll need to be comfortable communicating ideas to various audiences through presentations, whiteboarding, architecture discussions, and platform demonstrations.

• 5+ years in a customer-facing pre-sales, technical architecture, or consulting role

任职要求

• Comfortable programming in and debugging at least one of Python, Scala, Java, SQL, or R

• Have built solutions with public cloud providers, such as AWS, Azure, or GCP

• Data Engineering technologies (e.g., Spark, Hadoop, Kafka)

• Data Warehousing (e.g., SQL, OLTP/OLAP/DSS)

• Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)

• [Preferred] Degree in a quantitative discipline (e.g., Computer Science, Applied Mathematics, Operations Research, etc.)

• Nice to have: Databricks Certification

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(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 $139,700 — $247,300 USD

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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