Senior Data Engineer (AI-Native) — Data Layer

AI开发工程限定地区（需当地身份）

公司Proton

薪资未公开

工作地点Albania, Andorra, Anguilla, Antigua and Barbuda, Argentina, Aruba, Austria, Bahamas, Barbados, Belarus, Belgium, Belize, Bermuda, Bolivia, Bonaire, Sint Eustatius and Saba, Bosnia and Herzegovina, Brazil, Bulgaria, Cayman Islands, Chile, Colombia, Costa Rica, Croatia, Cuba, Czechia, Denmark, Dominica, Dominican Republic, Ecuador, El Salvador, Estonia, Falkland Islands (Malvinas), Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Grenada, Guatemala, Guernsey, Guyana, Haiti, Holy See (Vatican City State), Honduras, Hungary, Iceland, Ireland, Isle of Man, Italy, Jamaica, Jersey, Kosovo, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Mexico, Moldova, Monaco, Montenegro, Montserrat, Netherlands, Nicaragua, North Macedonia, Norway, Panama, Paraguay, Peru, Poland, Portugal, Puerto Rico, Romania, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, San Marino, Serbia, Slovakia, Slovenia, South Georgia and the South Sandwich Islands, Spain, Suriname, Svalbard and Jan Mayen, Sweden, Switzerland, Trinidad and Tobago, Turks and Caicos Islands, Ukraine, United Kingdom, Uruguay, Venezuela, Virgin Islands, British, Virgin Islands, U.S., Åland Islands

地域资格限定地区（需当地身份）

时区要求日间重叠约 4 小时，基本正常作息

用工类型Full Time

发布时间今天

数据来源Himalayas

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注意地域限制：该职位明确限定在 Albania、Andorra、Anguilla、Antigua and Barbuda、Argentina、Aruba、Austria、Bahamas、Barbados、Belarus、Belgium、Belize、Bermuda、Bolivia、Bonaire, Sint Eustatius and Saba、Bosnia and Herzegovina、Brazil、Bulgaria、Cayman Islands、Chile、Colombia、Costa Rica、Croatia、Cuba、Czechia、Denmark、Dominica、Dominican Republic、Ecuador、El Salvador、Estonia、Falkland Islands (Malvinas)、Faroe Islands、Finland、France、Germany、Gibraltar、Greece、Grenada、Guatemala、Guernsey、Guyana、Haiti、Holy See (Vatican City State)、Honduras、Hungary、Iceland、Ireland、Isle of Man、Italy、Jamaica、Jersey、Kosovo、Latvia、Liechtenstein、Lithuania、Luxembourg、Malta、Mexico、Moldova、Monaco、Montenegro、Montserrat、Netherlands、Nicaragua、North Macedonia、Norway、Panama、Paraguay、Peru、Poland、Portugal、Puerto Rico、Romania、Saint Kitts and Nevis、Saint Lucia、Saint Vincent and the Grenadines、San Marino、Serbia、Slovakia、Slovenia、South Georgia and the South Sandwich Islands、Spain、Suriname、Svalbard and Jan Mayen、Sweden、Switzerland、Trinidad and Tobago、Turks and Caicos Islands、Ukraine、United Kingdom、Uruguay、Venezuela、Virgin Islands, British、Virgin Islands, U.S.、Åland Islands 招聘。如果你是位于中国大陆的求职者，通常需要当地工作身份才能投递，或需与雇主确认是否接受独立合同（Contractor）形式合作。

关于本页中文：职位描述由本机离线模型翻译，属机器翻译，供快速判断用；正式沟通与投递请以英文原文为准。官方翻译通道恢复后会自动重译升级。

高级数据工程师 (AI-Native) 关于我们的数据层 Proton 正在为批发分销构建人工智能操作系统，嵌入了几乎所有地球上的物理产品移动的工作流程。分销是一家9万亿美元的行业，运行的软件已经被困在过去几十年里大多数工具创造了更多工作比它们消除的。我们将 CRM,PIM,电子商务 AI 和订单与引用输入 AI 集成到一个平台上，有一个数据层和一个人工智能大脑，所以代表们花费时间深化客户关系，而不是输入数据。我们聘请具有高代理性和高度紧迫性的人员。在 Proton,每个人都是一位拥有终端问题和快速运送 AI 原生软件的构建者。平均 proton 客户报告每花费美元的利回报3倍，每月额外的一天销售，以及30年来任何技术投资的最佳 ROI.从家族拥有的商店到公开交易企业中，数百家领先分销商在普罗顿上运营。我们得到了 Felicis Ventures (Twitch,Shopify,OpenDoor) 和电池风险公司的支持。如果你想建立出如何数万亿美元的物理商品通过经济流动的系统，Proton 是这样做的地方。角色我们正在聘请一名高级数据工程师来拥有和发展我们的数据层。你将拥有每个 Proton 产品和人工智能大脑构建的统一基础。你将拥有管道和架构：金牌式层（原料 →精炼 →策划）,从广泛的系统中摄入，服务整个公司都取决于它。我们在大量投资使数据层更大更好，这个角色适用于谁想做手动的建设和塑造下一步。两个事情使这一职位与标准的数据工程开放不同：· 你是一个人工智能本土运营商，而不是一个管道作者。普罗顿的每个工程师都用了克劳德代码和其他代理工具作为一流合作伙伴。我们预计将采用人工智能重力建造和运输管道，模型和迁移你指导代理人，验证输出，并做出他们无法判断的电话。· 你拥有所有东西运行的层。当人工智能给出错误答案或数字不匹配源头时，后踪会带回数据。你的正确性最终结束摄入，建模，调整以及其他团队所依赖的合同。地点：欧洲，远程。有意义的日期

查看英文原文

Senior Data Engineer (AI-Native) — Data Layer
About Us
Proton is building the AI operating system for wholesale distribution, embedded in the workflows that move nearly every physical product on the planet. Distribution is a $9 trillion industry, and the software that runs it has been stuck in the past for decades — most tools create more work than they eliminate. We unify CRM, PIM, eCommerce AI, and Order & Quote Entry AI into one platform with one data layer and one AI brain, so reps spend their time deepening customer relationships, not entering data.
We hire people with high agency and high urgency. At Proton, everyone is a builder who owns problems end to end and ships AI-native software faster than anyone else in the category.
The median Proton customer reports 3x profit return per dollar spent, an extra day of sales per rep per month, and “the best ROI of any tech investment in 30 years.” Hundreds of leading distributors — from family-owned shops to publicly-traded enterprises across, industrial, HVAC, electrical — run on Proton. We’re backed by Felicis Ventures (Twitch, Shopify, Opendoor) and Battery Ventures.
If you want to build the systems that shape how trillions of dollars of physical goods move through the economy, Proton is the place to do it.
The Role
We're hiring a Senior Data Engineer to own and grow our Data Layer — the unified foundation that every Proton product and our AI brain are built on. You'll own the pipelines and architecture end to end: the medallion-style layers (raw → refined → curated), ingestion from a wide range of systems, and the serving the whole company depends on. We're investing heavily to make the Data Layer bigger and better, and this role is for someone who wants to do the hands-on building and shape where it goes next.
Two things make this role different from a standard data engineering opening:

You're an AI-native operator, not a pipeline author. Every engineer at Proton uses Claude Code and other agentic tools as first-class collaborators. We expect pipelines, models, and migrations to be built and shipped with heavy AI leverage — you guide the agents, validate the output, and make the judgment calls they can't.

You own the layer everything runs on. When the AI gives a wrong answer or a number doesn't match the source, the trail leads back to the data. You own correctness end to end — ingestion, modeling, reconciliation, and the contracts other teams depend on.

Location: Europe, remote. Meaningful daytime overlap with our Boston (EST) team required.
What You'll Do

Own the Data Layer end to end: ingestion from file-, event-, and API-based sources; the medallion-style model (raw → refined → curated); and the serving layer that powers the product and the AI brain.

Build and operate the ingestion and transformation pipelines that power the Data Layer, using a modern orchestration framework and cloud data warehouse.

Ingest and reconcile large, messy, real-world data across many source types and shapes — batch files, streaming events, and APIs.

Model data across medallion layers so it's trustworthy, queryable, and stable for downstream teams and the AI.

Help take the Data Layer to the next level — better architecture, better tooling, more scale, more sources — and have a real say in what that looks like.

Operate AI coding agents (Claude Code and similar) at a high level: scope work, structure context, run agents in parallel where it makes sense, and ship reviewed, production-quality output.

Build the systems that make data trustworthy — validation, reconciliation, lineage, backfills, idempotent and incremental loads — so downstream teams and the AI don't inherit silent errors.

Partner with backend, AI, and product engineers (and occasionally customers' IT teams) to define the data contracts they build on.

Requirements

7+ years hands-on as a data engineer with real, demonstrable production ownership — pipelines and data models serving real users at scale.

Strong fundamentals. You understand what your code and your queries are doing and why. You can read a query plan, reason about a slow or expensive pipeline, and debug a data-correctness bug to its root.

Strong programming and SQL skills. You build efficient pipelines, schemas, and queries, and can model data for both transactional and analytical access patterns.

Hands-on orchestration experience, building reliable ingestion/ELT pipelines against messy upstream sources.

Experience with a cloud data warehouse and a major cloud platform.

Experience ingesting from multiple source types: file-based, event/streaming, and API-based.

Solid grasp of data-consistency failure modes — partial loads, late or out-of-order data, idempotency, backfills, schema drift.

Daily, hands-on use of agentic dev tools (Claude Code, Cursor agent mode, Codex, or equivalent) to ship real work. You can talk concretely about how you structure prompts, manage context, parallelize agents, and verify their output.

Ownership and judgment. You take data systems from idea to production and exercise good taste on what to build and what to cut.

Startup mindset and strong communication — pragmatic, fast, biased to ship, and able to explain data decisions to engineers, PMs, and customers in writing.

English at C1 or above.

Big Plus

Deep cloud data warehouse experience and modern transformation tooling.

Streaming / event ingestion at scale.

Medallion or lakehouse architecture experience on large, multi-source data.

Experience integrating enterprise sources such as ERP (Epicor Eclipse, Prophet 21) or ecommerce systems, and reconciling messy transactional data.

Building data systems that feed AI/ML or agentic products — serving/feature layers, retrieval, or data contracts for model inputs.

Prior experience at an early-stage SaaS startup.

Originally posted on Himalayas

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