高级数据工程师
Senior Data Engineer
### **✨ 一个平台，开启无限机遇**
最好的工作一直集中在世界最富裕的少数城市中。但人才无处不在。Oyster致力于缩小这一差距——打造一个全球就业平台，让公司可以随时随地雇佣、支付并关怀优秀的人才。
我们证明了高性能文化不需要办公室。自2020年以来，我们分布在60多个国家，已经构建出被行业不断关注的东西：
- 在TIME和Statista的2026年《美国顶级WorkTech公司》榜单中位列**第10名（共250家）** [https://www.oysterhr.com/library/oyster-hr-named-10-of-americas-top-worktech-companies-of-2026-by-time]
- 被Newsweek评为[2026年美国最棒的初创公司工作场所之一] [https://www.oysterhr.com/library/oyster-2026-newsweek-award]
- 在雇主代理、全球雇佣、多国薪酬和HR合规领域，被评为[G2 2026年春季领导者] [https://www.oysterhr.com/library/oyster-named-best-roi-for-any-global-employment-platform-for-g2-spring-2026]
- 唯一一家获得**B Corp认证**的全球雇佣平台 ~ 自2023年起独立验证
其中两项排名从外部衡量了我们的业务影响。一项衡量了我们员工在这里工作的感受。它们指向了同一个方向 ~ 因为在Oyster，文化和绩效不是两个不同的话题。它们是同一个话题。
我们才刚刚开始。如果你希望与那些和你一样关心工作的人一起，做出职业生涯中最出色的工作，我们欢迎你申请。
### **👩💻 职位描述**
**地点：** 虽然该职位是在特定地点发布的，但Oyster的所有职位都是完全远程的，你可以永远在家工作。为了给新员工创造最佳体验，该职位要求你位于UTC−6到UTC+3时区。
Oyster的数据工程团队正在构建基础的AI平台层，使Oyster各团队能够开发、部署和运营安全、生产级的AI能力。作为专注于AI平台的高级数据工程师，你将处于数据工程、平台工程和应用AI的交汇点。你将构建数据管道、服务、集成和可重用的平台功能，以支持Oyster中各种AI用例。
你将利用Oyster现有的AWS和Snowflake数据平台，使企业数据对AI来说可访问、可靠、安全且有用，支持诸如LLM、RAG、嵌入、向量搜索、AI代理、工具等能力。
查看英文原文
### **✨ One platform, a whole world of opportunity**
The best jobs have always clustered in a handful of the world's wealthiest cities. But talent is everywhere. Oyster set out to close that gap - building a global employment platform that lets companies hire, pay, and care for brilliant people anywhere.
We're proof that a high-performing culture doesn't need an office. Distributed across 60+ countries since 2020, we've built something the industry keeps noticing:
- Ranked **#10 of 250** on TIME and Statista's 2026 list of [America's Top WorkTech Companies](https://www.oysterhr.com/library/oyster-hr-named-10-of-americas-top-worktech-companies-of-2026-by-time)
- Named one of [America's Greatest Startup Workplaces 2026](https://www.oysterhr.com/library/oyster-2026-newsweek-award) by Newsweek
- A [G2 Spring 2026 Leader](https://www.oysterhr.com/library/oyster-named-best-roi-for-any-global-employment-platform-for-g2-spring-2026) across Employer of Record, Global Employment, Multi-country Payroll, and HR Compliance
- The only **B Corp-certified** global employment platform ~ independently verified since 2023
Two of those rankings measured our business impact from the outside. One measured how our own people feel about working here. They landed in the same place ~ because at Oyster, culture and performance aren't separate conversations. They're the same one.
And we're just getting started. If you want to do the best work of your career alongside people who care as much as you do, we'd love for you to apply.
### **👩💻 The Role**
**Location:** While this position is posted in a specific location, all of Oyster’s positions are fully remote and you can work from home. Forever. To create the best experience for our new hire, this role requires you to be based within UTC−6 to UTC+3.
Oyster’s Data Engineering team is building the foundational AI platform layer that will enable teams across Oyster to develop, deploy, and operate secure, production-grade AI capabilities. As a Senior Data Engineer focused on AI Platform, you’ll work at the intersection of data engineering, platform engineering, and applied AI. You’ll build the data pipelines, services, integrations, and reusable platform capabilities that power AI use cases across Oyster.
You’ll leverage Oyster’s existing AWS and Snowflake data platform to make enterprise data accessible, reliable, secure, and useful for AI, supporting capabilities such as LLMs, RAG, embeddings, vector search, AI agents, tool calling, and AI workflows.
This is not a traditional data engineering role focused primarily on analytics pipelines or reporting. You’ll help define and build the data and platform foundations that let AI systems move from experimentation to reliable production, working closely with Engineering, Product, IT, and other teams across Oyster.
**Key Responsibilities**
- Design and build data pipelines and platform capabilities that support AI applications, knowledge systems, and AI workflows.
- Build and maintain data and knowledge pipelines for ingestion, transformation, chunking, embeddings, retrieval, vector search, metadata, and knowledge management.
- Develop secure, reusable ways for AI systems to access enterprise data and systems using APIs, MCP, tool calling, and similar patterns.
- Build reusable services, libraries, frameworks, and developer tooling that make it easier for engineering teams to build and productionize AI capabilities.
- Apply strong data engineering practices around data modeling, data quality, lineage, access, reliability, and governance to AI-related data and systems.
- Help establish patterns for AI deployment, observability, evaluation, and lifecycle management, including quality, latency, reliability, security, and cost.
- Partner with engineers and stakeholders to take AI use cases from prototype to production, ensuring the underlying data and infrastructure are scalable and maintainable.
- Ensure AI platform capabilities meet Oyster’s security, privacy, access control, and data governance requirements.
- Evaluate emerging AI and data technologies and determine where they can create meaningful value for Oyster.
**Core Requirements**
- 5+ years of experience in data engineering, platform engineering, backend engineering, ML engineering, or a related discipline, with experience building and operating production systems.
- Strong Python and SQL skills.
- Strong data engineering fundamentals, including data pipelines, data modeling, data quality, orchestration, and secure data access.
- Experience with Snowflake, Databricks, or comparable modern data platforms, and tools such as dbt, Airflow, or similar.
- Hands-on experience building or supporting production systems using LLMs / generative AI.
- Practical experience with one or more of RAG, embeddings, vector search, tool/function calling, AI agents, or enterprise knowledge systems.
- Experience building data or platform capabilities that are reusable across teams, rather than only developing one-off solutions.
- Experience taking systems from experimentation to reliable production, including considerations around scalability, observability, performance, and maintainability.
- Solid understanding of security, authentication/authorization, privacy, and data governance, particularly in the context of enterprise data.
- Strong communicator who can work across Engineering, Product, and IT to turn ambiguous AI and data problems into practical engineering solutions.
**Bonus**
- Experience with AWS Bedrock or other managed foundation-model platforms.
- Hands-on experience with MCP (Model Context Protocol) or similar approaches for connecting AI systems to enterprise tools and data.
- Experience with LLM evaluation, observability, monitoring, or AI quality.
- Experience with LangChain, LangGraph, or similar frameworks.
- Experience with vector databases or search technologies.
- Experience implementing AI security, governance, or responsible AI practices.
- Experience building internal developer platforms, SDKs, APIs, or reusable infrastructure for engineering teams.
- Experience working across data engineering and AI/ML platform environments.
#### **You'll also need**
- A reliable home internet connection (or be able to get one).
- Fluent English language skills.
### **How we work together at Oyster**
Our values guide the work we do, the decisions we make, and the culture that makes Oyster what it is. We make it happen—progress is our default setting. We drive change, we build and give trust, and we move as one united team.
Our mission is to create a more equal world of work: helping companies everywhere hire, pay, and care for talent anywhere. Everything we do ladders up to our mission. We embrace asynchronous, collaborative work and share how we operate in the [Oyster Public HQ](https://oysterhr.notion.site/Welcome-to-The-Reef-Oyster-s-Open-Source-Employee-Guide-fc482e3f107c4afd8c85ed217f1d0c1d) so other global teams can learn from us.
### **How YOU work**
With diverse locations, cultures, and needs, we created [How YOU Work;](https://oysterhr.notion.site/How-YOU-work-ac16c1932e314ffd8cb693e332458395) a program supporting your whole human experience at Oyster:
- **Work from anywhere:** Oyster has no borders or HQ. As long as work is timely, your team is supported, and you're authorized to work where you live, you can work from anywhere.
- **Paid time off:** Enjoy 40 days off per year (including holidays and vacation), or more if required by your country.
- **Mental health support:** Access [Plumm](https://oysterhr.notion.site/Plumm-3b5e7e70dec6428e975f68f25972cfb7), our mental well-being service.
- **Wellbeing allowance:** Each month, receive a wellbeing allowance in your ThanksBen wallet to spend on a wide range of options.
- **Flexible parental leave:** All new parents are eligible for at least three months’ paid leave, with job protection for up to 12 months or as required locally.
- **WFH stipend:** Receive a stipend for your laptop and home office equipment to get you set up quickly.
### **✨ The best jobs should be available to everyone**
We embrace diverse perspectives and intentionally build our product and company with an inclusive, global mindset. We encourage you to apply, even if you don’t meet every criterion, and are committed to a trust-based, thriving environment.
Oyster is committed to ensuring equal opportunity of employment for qualified persons with disabilities and actively fosters an inclusive work environment. If you require reasonable accommodations throughout the recruiting process, please email [jobs@oysterhr.com](mailto:jobs@oysterhr.com) with the subject line: Interview Accommodations.
Our available positions are on our careers page. Our team will only contact you from an @ _oysterhr.com_ email, and **we will never ask for money as part of an interview process or job offer.** If you receive a suspicious email about Oyster jobs or are directed to a site other than [www.oysterhr.com/careers](http://www.oysterhr.com/careers), please report it via our [Compliance and Ethics Helpline](https://faceup.com/c/8tpzyyye).