Installing build-cli
Step-by-step guide to installing and verifying build-cli, the DMDQP team's internal wrapper around Claude Code, on any platform.
You will be able to set up and use Claude Code via build-cli, choose the right AI tool for data engineering tasks, and apply AI-assisted code review and pipeline development to your daily work.
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Step-by-step guide to installing and verifying build-cli, the DMDQP team's internal wrapper around Claude Code, on any platform.
Install Claude Code via Roche build-cli — the mandatory starting point for internal AI tool access
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A 15-minute guided walkthrough of a real first session with build-cli, from opening your terminal to getting useful output.
Get productive in your first Claude Code session — project setup, CLAUDE.md, and key workflows
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A decision guide for choosing between Gemini (Google Suite) and build-cli (Claude Code) for DMDQP tasks, with a quick-reference table and key differences.
Understand when to use Claude Code, Copilot, or a chat interface for different task types
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A step-by-step workflow for using build-cli to produce a structured, systematic SQL code review for dbt models, stored procedures, or ad hoc query scripts.
Apply AI-assisted SQL review to catch data quality issues and anti-patterns before they reach production
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A step-by-step workflow for using build-cli to perform a structured code review of Python or PySpark data pipelines before they reach a human reviewer or quality gate.
Use Claude Code to review Python ETL and pipeline code for correctness and maintainability
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A ready-to-use CLAUDE.md template for Python or PySpark ETL pipeline projects (AWS Glue, Airflow, or plain Python) — giving build-cli persistent context about tech stack, pipeline structure, conventions, and data quality requirements.
Configure a CLAUDE.md for your ETL pipeline project so every Claude Code session has project context
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Use this prompt to generate SQL or PySpark transformation code from a source-to-target mapping specification — field by field, with ambiguous rules flagged as inline comments.
Use the transformation code-gen prompt to scaffold data transformation logic from a spec