Model data and build dbt pipelines from staging to marts.
npx skills add https://github.com/borghei/Claude-Skills --skill analytics-engineer
Please help me install this Agent Skill. Skill: analytics-engineer Source: https://github.com/borghei/Claude-Skills/tree/main/data-analytics/analytics-engineer Command: npx skills add https://github.com/borghei/Claude-Skills --skill analytics-engineer
Analytics teams often struggle to design scalable, maintainable analytics pipelines that produce trusted data for decision-making. This Skill provides a framework for data modeling, dbt development, semantic layer management, and documentation to accelerate accuracy and governance.
Initialize and structure a dbt analytics project with standard models and tests, then integrate with your warehouse and BI tools.
High-intent search queries and answers about installing and using this skill.
To structure dbt data pipelines for scalability, separate models into staging, intermediate, and marts layers. This architecture ensures clean transformations, manageable dependencies, and trusted analytics outputs.
A semantic layer in analytics engineering defines consistent metrics for BI dashboards. You need it to govern data definitions, prevent metric mismatches across reports, and maintain trusted analytics pipelines.
Building an end-to-end analytics stack involves modeling source data in SQL, developing dbt pipelines through staging to marts, and integrating a semantic layer for BI dashboards to ensure reproducible data flows.
Yes, you can use SQL and dbt to manage data warehouse schema design. This approach enables scalable data modeling, automated testing frameworks, and pipeline governance directly within your modern data stack.
The best way to add testing and documentation to analytics pipelines is integrating dbt frameworks. This enforces data quality checks and auto-generates project docs, accelerating accuracy and governance.
AradotsoBuild a semantic context layer for AI agents querying data warehouses.
JaviMontanoDesign enterprise BI architecture with a semantic-layer-first approach across multi-tool environments.
davekim917Standardize dbt project structure, naming, tests, and documentation.
niitsAnswer natural language questions by querying dbt Semantic Layer metrics and executing SQL.
