领域
Data Engineering
技能档案
ACID transactions, time travel, schema evolution, table formats for data lakes
角色数
1
包含此技能的角色
级别数
5
结构化成长路径
必要要求
5
其余 0 个可选
Data Engineering
Data Lakehouse
2026/3/17
选择当前级别并对比期望。下方卡片显示晋升所需掌握的内容。
表格展示从初级到首席的技能深度变化。点击行查看详情。
| 角色 | 必要性 | 描述 |
|---|---|---|
| Data Engineer | 必要 | Understands the fundamentals of Delta Lake / Apache Iceberg. Applies basic practices in daily work. Follows recommendations from the team and documentation. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Data Engineer | 必要 | Independently implements data pipelines with Delta Lake/Apache Iceberg. Optimizes performance. Ensures data quality. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Data Engineer | 必要 | Designs data architecture with Delta Lake/Apache Iceberg. Optimizes for big data. Implements data governance and quality frameworks. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Data Engineer | 必要 | Defines Delta Lake/Iceberg standards: table format selection, partitioning strategy, compaction schedules. Implements time-travel for data debugging and schema enforcement. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Data Engineer | 必要 | Designs open table format strategy: Delta Lake vs Iceberg vs Hudi, catalog integration (Unity/Nessie), cross-engine interop. Defines migration path from Hive tables. |