高级AI数据工程师 - 葡萄牙
Senior Data Engineer AI - Portugal
我们寻找一位高级数据工程师，其价值观与我们一致：注重软件工程工艺、务实、专业。您应理解，数据工程本质上是大规模应用的优秀软件工程，需严谨并以生产环境为导向。
这不是一个独立的数据岗位。您将作为我们软件交付团队的一员，帮助客户在更广泛的现代化、平台、数据和AI准备项目中构建生产级数据基础。Databricks是我们主要的数据工程平台，您需要能够熟练使用；但目标始终是构建持久、精良的数据系统，而非工具推广。
要求
当前或近期经验：
数据工程师、高级数据工程师、数据平台工程师或Databricks工程师职位。
必备 – Databricks在生产环境中的使用
有在生产环境中使用Databricks的经验，包括Delta Lake、Spark/PySpark、Unity Catalog或生产湖仓项目。
必备 – 强大的软件工程实践
具备Python、测试、Git、CI/CD、代码审查、部署或基础设施即代码方面的丰富经验。
必备 – 构建并维护可靠的流水线
有数据质量、编排、监控、血缘关系、模式演进或数据契约方面的经验。
必备 – 咨询与协作
有客户交付、利益相关者对接、现代化项目、指导或跨工程团队工作的经验。
优先 – 云平台
有AWS或Azure的经验。两种云平台均可接受。
加分项 – 用于生产环境的ML/AI数据
有ML/AI特征流水线、MLflow、模型血缘关系、嵌入、向量搜索、检索或评估数据集方面的经验。
最初发布于Himalayas
查看英文原文
We are looking for a Senior Data Engineer who shares our values of software craftsmanship, pragmatism, professionalism. You understand that data engineering is, at its core, great software engineering, applied at scale, with rigour, and with production in mind.
This is not a standalone data role. You will work as part of our software delivery teams, helping clients build production-grade data foundations in broader modernisation, platform, data, and AI-readiness engagements. Databricks is our primary data engineering platform, and you will be expected to use it fluently; but the goal is always durable, well-crafted data systems, not tool advocacy.
Requirements
Current or recent experience:
Data Engineer, Senior Data Engineer, Data Platform Engineer, or Databricks Engineer role.
Essential – Databricks in production
Hands-on experience with Databricks in production, including Delta Lake, Spark/PySpark, Unity Catalog, or production lakehouse projects.
Essential – Strong software engineering practices
Strong experience with Python, testing, Git, CI/CD, code review, deployment, or Infrastructure as Code.
Essential – Builds and operates reliable pipelines
Experience with data quality, orchestration, monitoring, lineage, schema evolution, or data contracts.
Essential – Consulting and collaboration
Experience with client delivery, stakeholder engagement, modernisation projects, mentoring, or working across engineering teams.
Preferred – Cloud
Experience with AWS or Azure.
Either cloud is acceptable for the role.
Differentiator – Data for production ML/AI
Experience with ML/AI feature pipelines, MLflow, model lineage, embeddings, vector search, retrieval, or evaluation datasets.
Originally posted on Himalayas