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WayneBanksy
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staff-analytics-engineer

Design dbt data models, tests, documentation, and semantic definitions for financial workflows.

1|Updated Apr 27, 2026
Search Tags:#testing#documentation#data modeling#dbt#financial metrics#semantic layer
One-click install
npx skills add https://github.com/WayneBanksy/wayneys_claude --skill staff-analytics-engineer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: staff-analytics-engineer
Source: https://github.com/WayneBanksy/wayneys_claude/tree/main/skills/staff-analytics-engineer
Command: npx skills add https://github.com/WayneBanksy/wayneys_claude --skill staff-analytics-engineer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

It provides specialized guidance for designing and managing dbt projects focused on financial and analytical models, ensuring consistency, correctness, and auditability.

Core Features & Use Cases

  • Model Architecture Design: Assists in structuring staging, intermediate, and mart layers adhering to best practices.
  • Data Testing & Documentation: Guides on defining column descriptions, writing tests, and ensuring data quality.
  • Semantic Layer & Metrics: Supports creation of business metrics using MetricFlow, and setup of source freshness and snapshots.
  • Use Case: A team implementing a new financial metric can use this skill to define the metric in MetricFlow, add relevant tests, and document the schema efficiently.

Quick Start

Request dbt model setup for a new sales reporting star schema.

Frequently Asked Questions about staff-analytics-engineer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I structure dbt data models for financial reporting?▼

Dbt data modeling for financial workflows involves structuring staging, intermediate, and mart layers to ensure consistency and auditability. This approach separates raw transformations from presentation-ready marts.

What is the best way to define financial metrics using MetricFlow?▼

Defining financial metrics with MetricFlow involves creating semantic layer definitions within your dbt project. This enables consistent calculation, testing, and documentation of business metrics for reliable reporting.

How do I add tests and documentation to a dbt project?▼

Adding tests and documentation to a dbt project requires defining column descriptions and writing data tests in schema files. This ensures data quality and clear context for downstream analytical models.

Does dbt support source freshness monitoring and snapshots for analytics?▼

Yes, dbt supports source freshness monitoring and snapshots for analytics. Setting up these features tracks data pipeline health and maintains historical records for compliant financial reporting.

Can I use this approach to build a sales reporting star schema in dbt?▼

Yes, you can use this dbt approach to build a sales reporting star schema. It guides you through structuring data models, adding tests, and documenting the schema for financial and analytical workflows.

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