data-engineering SKILL.md skillA
data-engineering from yuecao365/offercome is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add yuecao365/offercome/data-engineering@git:20260920.a4843f5Pins git:20260920.a4843f5 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- yuecao365/offercome
- Path
src/lib/mock-interviews/skills/data-engineering/SKILL.md- Versions recorded
- 4
- Latest version
- git:20260920.a4843f5, committed Sep 20, 2026
- First version recorded
- Sep 7, 2026
- Size
- 8,697 bytes
- Repository stars
- 24
- License
- MIT
数据工程怎么面：数仓建模、离线与实时链路、调度、数据质量、湖仓。数据开发与数仓岗读。.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
## 面试官在意什么 数据开发 / 数仓工程师负责把业务数据变成可信、可用、可持续交付的数据资产：建模分层、写离线和实时任务、维护调度依赖、保障数据质量与 SLA、控制存储与计算成本。真实面试里被问最多的是建模判断（这张表该怎么设计、口径谁定）、链路事故（数据晚了、错了、重了怎么查）、以及性能与成本（任务跑不完、集群费用涨了怎么办）。面试官最在意三件事：一是有没有真正对数据准确性负过责——出过事故、补过数、回溯过口径；二是建模能不能落到业务，而不是背 Kimball 四步；三是对链路全貌的理解：从埋点采集到报表，哪一环出问题会怎么表现。 校招侧重 SQL 功底（窗口函数、多表关联、去重与留存计算）、数仓分层与维度建模的基本概念、Hive/Spark 的执行原理；社招侧重实时数仓与湖仓选型、数据质量体系、任务治理与成本优化、跨团队口径协调。一线大厂近年明显更看重"数据资产化"与"降本"，外企则更关注 pipeline 的工程规范（测试、版本、幂等）。 怎么问才像这个方向的面试官： - 所有题目都要挂在"数据准确性"或"链路事故"上：不问"什么是拉链表"，问"这个场景用不用拉链表、不用的话怎么回溯"。 - 必须结合候选人的数据规模：日增 GB 级与 PB 级的最优方案完全不同，先问清规模再评判方案对错。 - 不要考组件版本与参数名，考执行原理与排查顺序；候选人说"调参数"要追它改变了执行的哪一步。 - 建模题要给出具体业务场景（订单、日志、用户）与冲突需求，让候选人现场定粒度、说取舍。 - 2026 年数据工程的架构主线是批流一体的湖仓：开放表格式（Iceberg 一类）成了跨引擎的存储标准，实时链路靠 CDC 与流处理引擎直接写湖，AI 场景对数据新鲜度提出了新的 SLA。面试官会追候选人怎么统一批与流、表格式解决了什么、新鲜度怎么量。 ## 项目 / 实习怎么深挖 简历上出现下面这类经历时从哪里切、追什么。追到候选人能说出机制、数字的来源与一次真实的故障或取舍才算实；只有框架名与结论、说不出自己那一段的，记为危险信号。通用的追问方法见 project-deep-dive。 - 简历出现"搭建数仓" → 追分了几层、粒度怎么定、公共层复用率、你自己建的表被多少下游用 - 简历出现实时数仓 / Flink → 追状态大小、checkpoint 间隔与耗时、迟到数据处理方式、出过什么事故 - 简历出现"数据质量体系" → 追规则数量、阻断率、误报率、最近一次靠它拦住的问题 - 简历出现"性能优化 X 倍" → 追优化前后耗时、怎么定位瓶颈、改了什么、数据量多大 - 简历出现 Iceberg / Hudi / Paimon → 追为什么迁、迁前痛点、小文件与元数据怎么治理 …
Read the whole file at its exact version.
How to install
mdr add yuecao365/offercome/data-engineering@sha256:3d724cee69b6ff34The line at the top of this page pins the label git:20260920.a4843f5, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_tlc3qx5ujhlw74hl)
6 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 4 versions of this file, between Sep 7, 2026 and Sep 20, 2026, about one every 4 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260920.a4843f5 latest | 2026-09-20 | a4843f5 | 8,697 B | A | view · diff |
| git:20260919.2ea5304 | 2026-09-19 | 2ea5304 | 10,198 B | A | view · diff |
| git:20260908.a2a662c | 2026-09-08 | a2a662c | 12,019 B | A | view · diff |
| git:20260907.4739619 | 2026-09-07 | 4739619 | 11,178 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (8697 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
yuecao365/offercome · 24 stars · license MIT · pushed 2026-10-01 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_tlc3qx5ujhlw74hl GET https://markdownregistry.com/api/v1/resolve?ref=yuecao365/offercome/data-engineering GET https://markdownregistry.com/api/v1/blob/3d724cee69b6ff349cba22a36c863ddd89793ce57441598a4c43f23a64d5fe16
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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