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cloud-data-infra

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Mis à jour5 juillet 2026 à 11:17

Umbrella skill for where data pipelines run and what they cost — AWS/GCP/Azure infrastructure (S3/GCS/ADLS layout, BigQuery/Redshift/Snowflake selection, IAM, managed-service choice, performance tuning) and cost control (bytes scanned, partition pruning, slot/credit management, storage tiering, budgets and alerts). Use this whenever the topic is cloud data infrastructure or the cloud data bill. This skill ROUTES to the focused sub-skills (cloud-infra-data, cost-optimization-data) and pulls in both when a task spans architecture and cost. Trigger on: deploying a pipeline to cloud, choosing between managed warehouses, bucket/partition layout, IAM for data access, "our BigQuery bill jumped", expensive queries, or slot/credit utilization.

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Methasit-Pun

Methasit-Pun/data_engineer_claude_skills

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Métiers associésSOC

Basé sur la classification professionnelle SOC

Développeurs de logicielsProfessions informatiques et mathématiques·SOC 15-1252

SKILL.md

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name

cloud-data-infra

description

Cloud Data Infrastructure & Cost (Router)

This is a router skill. It groups the two skills covering cloud data infrastructure and its cost. Diagnose which sub-area(s) the task touches, then invoke the matching sub-skill(s) with the Skill tool.

How to route

If the task is about…	Invoke sub-skill
Provisioning and architecture: S3/GCS/ADLS partitioning, BigQuery slots, Redshift Spectrum, Snowflake warehouses, IAM/cross-account access, managed-service selection, cloud performance tuning	`cloud-infra-data`
The bill: query cost analysis, bytes scanned, partition pruning, slot reservation vs. on-demand, storage tiering, Snowflake credits, cost alerts and budgets	`cost-optimization-data`

Routing rules

These two almost always travel together. A "slow BigQuery query" is both a performance (cloud-infra-data) and a cost (cost-optimization-data) problem — invoke both.
"Our bill jumped" or a named expensive query → lead with cost-optimization-data (it starts by finding where the money goes), then cloud-infra-data for the structural fix.
Choosing/standing up a warehouse or storage layout → lead with cloud-infra-data, then cost-optimization-data to price the choice.
Invoke via the Skill tool by name, e.g. Skill(skill="cost-optimization-data"). Combine outputs; don't paraphrase from memory.

Related groups

Pipelines deployed onto this infra → [[data-pipelines]]
Query patterns that drive cost → [[data-modeling]]

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Methasit-Pun/data_engineer_claude_skills

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dbt-patterns

Methasit-Pun/data_engineer_claude_skills

dbt model design, ref chains, sources, tests, macros, incremental strategies, materializations, and documentation best practices. Use this skill whenever the user is writing or reviewing dbt models, configuring dbt tests, designing model layers (staging/intermediate/marts), asking about incremental models, choosing materializations, writing macros, setting up sources.yml, or troubleshooting dbt run/test failures. Also trigger when the user mentions dbt refs, lineage graphs, model dependencies, dbt Cloud, the dbt CLI, or when they want to transform data already in the warehouse using SQL. If the project uses dbt at all, this skill should be active for any transformation questions.

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Methasit-Pun/data_engineer_claude_skills

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name

cloud-data-infra

description

Cloud Data Infrastructure & Cost (Router)

How to route

If the task is about…	Invoke sub-skill
Provisioning and architecture: S3/GCS/ADLS partitioning, BigQuery slots, Redshift Spectrum, Snowflake warehouses, IAM/cross-account access, managed-service selection, cloud performance tuning	`cloud-infra-data`
The bill: query cost analysis, bytes scanned, partition pruning, slot reservation vs. on-demand, storage tiering, Snowflake credits, cost alerts and budgets	`cost-optimization-data`

Routing rules

These two almost always travel together. A "slow BigQuery query" is both a performance (cloud-infra-data) and a cost (cost-optimization-data) problem — invoke both.
"Our bill jumped" or a named expensive query → lead with cost-optimization-data (it starts by finding where the money goes), then cloud-infra-data for the structural fix.
Choosing/standing up a warehouse or storage layout → lead with cloud-infra-data, then cost-optimization-data to price the choice.
Invoke via the Skill tool by name, e.g. Skill(skill="cost-optimization-data"). Combine outputs; don't paraphrase from memory.

Related groups

Pipelines deployed onto this infra → [[data-pipelines]]
Query patterns that drive cost → [[data-modeling]]