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interlace.sh: Why We Built a Unified Abstraction
统一抽象层如何化解数据工程师面对2026年复杂工具链的困境，值得一读。
Consider what a data engineer has to learn before writing a single useful transformation on a typical 2026 data stack. dbt, for SQL models, sources, t…
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SiriusDeliver: Automating Data Warehouse Delivery at Tencent
腾讯如何用SiriusDeliver实现数据仓库交付自动化，一窥工业级数据工程的最新实践。
arXiv:2608.09185v1 Announce Type: cross Abstract: Enterprise data warehouses (DWs) support business-critical analytics, but warehouse task delivery re…
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Ask HN: Burned Tokens scented candle ideas
想体验AI训练的“烧焦味”？数据工程师的创意让LLM令牌变成蜡烛香气，烧焦吐司是首选方案。
The other day my relative, who is a data engineer, floated the idea of a scented candle that would smell like burned LLM tokens. His birthday is comin…
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Databricks Data and AI Summit 2026 as it was
Databricks峰会全景回顾，数据与AI融合趋势一网打尽，洞见Lakehouse与智能平台最新风向。
Article URL: https://medium.com/data-engineer-things/databricks-data-and-ai-summit-2026-as-it-was-2e146b77912a Comments URL: https://news.ycombinator.…
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The Data Recipe for Teaching AI New Skills [video]
AI技能训练数据配方的实战拆解，数据科学家与模型训练者的必看指南
Article URL: https://www.youtube.com/watch?v=I9F_VFfLTmM Comments URL: https://news.ycombinator.com/item?id=48771721 Points: 2 # Comments: 1
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Show HN: A dbt-first semantic assumption check for SQL changes
开源SQL变更语义检查工具，dbt优先，自动发现逻辑错误，防止生产事故。
Article URL: https://github.com/hiteshsundraaa/semzero-public-alpha-launch Comments URL: https://news.ycombinator.com/item?id=48582283 Points: 1 # Com…
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Trustworthy Self-Composable Big-Data-as-a-Service: An LLM-Orchestrated Multi-Agent Framework for Automated Data Engineering, AutoML, MLOps Deployment, and Drift-Aware Lifecycle Optimization
LLM编排多智能体实现大数据服务自组合，涵盖自动化数据工程、AutoML、MLOps及漂移感知生命周期优化，为AI基础设施提供高可信解决方案。
arXiv:2606.17915v1 Announce Type: cross Abstract: Big-Data-as-a-Service (BDaaS) platforms require re liable automation across data ingestion, cleaning…
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Linux Fundamentals for Data Engineering
数据工程师必看的Linux入门实操，从WSL安装到SSH远程连接与用户管理全流程。
Introduction As a data engineer, most of your work will happen on Linux servers. Whether you are managing databases, running data pipelines, or proces…
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Database Normalization via Dual-LLM Self-Refinement
双LLM相互精炼实现数据库自动化规范化，突破传统范式规则，AI赋能数据工程新思路。
arXiv:2508.17693v2 Announce Type: replace-cross Abstract: Database normalization is crucial to preserving data integrity. However, it is time-consumin…
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ETLs in the Era of AI and Sandboxes
探讨AI时代数据ETL与沙盒如何重塑数据处理流程，技术干货值得细读。
Article URL: https://zozo123.github.io/agentic-airbyte/ Comments URL: https://news.ycombinator.com/item?id=48431874 Points: 1 # Comments: 0
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Exploring Autonomous Agentic Data Engineering for Model Specialization
前沿论文：自主代理驱动数据工程，专精模型定制化训练新范式
arXiv:2605.30407v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated strong performance on general tasks, while often stru…
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Guiding LLM Post-training Data Engineering with Model Internals from Sparse Autoencoders
利用稀疏自编码器挖掘模型内部信号，为LLM强化学习数据工程提供全新无监督指引。
arXiv:2605.27354v1 Announce Type: cross Abstract: Model internals encode rich information about how a large language model (LLM) processes its trainin…
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How Grab is Using AI Agents to Boost Team Productivity
Grab数据工程团队用AI Agent破解协作难题，真实案例看如何提升生产力
Grab’s data engineering team had a problem that looks familiar to anyone who’s maintained shared infrastructure.
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Data-Centric AI Manifesto: How Data Quality Drives Modern AI
数据质量比模型规模更关键——这份宣言旗帜鲜明地指出，AI 的真正瓶颈不在算法，而在数据的清洁与结构，是时候将注意力从调参转向整理数据了。
Article URL: https://www.mdpi.com/2079-9292/15/9/1913 Comments URL: https://news.ycombinator.com/item?id=48161686 Points: 2 # Comments: 0