领域
Data Engineering
技能档案
dbt models, tests, macros, packages, incremental models, snapshots
角色数
4
包含此技能的角色
级别数
5
结构化成长路径
必要要求
20
其余 0 个可选
Data Engineering
Batch Processing
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 |
|---|---|---|
| Analytics Engineer | 必要 | Understands dbt project structure, models, and ref/source functions. Follows established patterns for writing SQL transformations and schema tests. Uses dbt run and dbt test commands following team CI/CD workflows. |
| BI Analyst | 必要 | Understands dbt basics and how it transforms raw data into BI-ready datasets. Follows team conventions for writing simple dbt models that feed dashboards. Uses dbt docs to understand data lineage and model dependencies. |
| Data Analyst | 必要 | Understands dbt fundamentals: models, tests, and documentation. Follows team patterns for building analytical transformations from staging to mart layers. Uses dbt-generated documentation to discover available datasets for analysis. |
| Data Engineer | 必要 | Creates dbt models: SELECT queries with ref() and source(), staging and mart models. Writes generic tests (unique, not_null). Understands DAG and dependencies between models. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Analytics Engineer | 必要 | Independently builds dbt transformation pipelines with incremental models, snapshots, and custom macros. Implements data quality tests with dbt-expectations and dbt-utils packages. Configures materializations and optimizes model performance. |
| BI Analyst | 必要 | Independently writes dbt models for BI reporting layer: metric definitions, aggregate tables, and dimensional models. Implements schema tests and data freshness checks. Configures dbt exposures to document downstream dashboard dependencies. |
| Data Analyst | 必要 | Independently builds dbt models for analytical datasets with proper testing and documentation. Implements Jinja macros for reusable transformation logic. Configures model materializations appropriate for analytical query patterns and data volume. |
| Data Engineer | 必要 | Designs dbt project: custom macros, incremental models, snapshots for SCD Type 2. Configures environments (dev/staging/prod). Optimizes models through materialization selection. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Analytics Engineer | 必要 | Architects data systems with dbt. Optimizes for big data. Implements data governance and quality frameworks. |
| BI Analyst | 必要 | Designs dbt project architecture for enterprise BI platform with semantic layer integration. Implements dbt Mesh patterns for cross-project model references. Architects multi-environment deployment strategies with slim CI and state-based builds. |
| Data Analyst | 必要 | Designs dbt transformation architecture for complex analytical domains. Implements advanced patterns: unit testing, contract enforcement, and version-controlled schema evolution. Mentors analysts on dbt best practices and efficient SQL transformation design. |
| Data Engineer | 必要 | Designs dbt architecture: multi-project setup, package management, custom generic tests. Implements unit tests for complex transformations. Optimizes performance: incremental + merge, partition-based. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Analytics Engineer | 必要 | Defines the organization's dbt project architecture: modular package structure, cross-project references, shared macros library. Implements standards for incremental models, snapshot strategies, and dbt environment management (dev/staging/prod). |
| BI Analyst | 必要 | Defines dbt development standards for BI organization. Establishes model naming conventions, testing requirements, and code review processes. Coordinates dbt governance across teams with shared macro libraries and package management strategies. |
| Data Analyst | 必要 | Defines dbt transformation standards across analytical teams. Establishes modeling layer conventions, testing coverage requirements, and deployment workflows. Drives adoption of self-service dbt development among analyst teams with proper guardrails. |
| Data Engineer | 必要 | Defines dbt standards: project structure, naming conventions, documentation requirements, PR review checklist. Implements dbt metrics layer and exposure definitions for data contracts. |
| 角色 | 必要性 | 描述 |
|---|---|---|
| Analytics Engineer | 必要 | Architects the enterprise dbt platform evolution strategy: multi-project mono-repo vs multi-repo, dbt mesh for cross-team dependencies, migration to dbt Cloud. Defines the roadmap for MetricFlow/Semantic Layer adoption to unify business metrics. |
| BI Analyst | 必要 | Defines enterprise dbt strategy and transformation platform architecture. Evaluates dbt Cloud vs Core trade-offs, Mesh adoption, and semantic layer integration paths. Shapes organizational data transformation governance aligned with data mesh principles. |
| Data Analyst | 必要 | Shapes enterprise dbt transformation strategy and analytical platform evolution. Drives organizational adoption of modern transformation patterns and tooling. Defines long-term dbt architecture roadmap with versioning, contracts, and cross-team collaboration models. |
| Data Engineer | 必要 | Designs transformation strategy: dbt for SQL transformations, Spark for complex processing, dbt mesh for multi-team. Defines governance for shared models and cross-project dependencies. |