# snowflake-data-engineering-cursorrules-prompt-file

Snowflake data engineering rules for Cursor: SQL standards, semi-structured VARIANT handling, declarative Dynamic Tables, and warehouse cost control.

- rule · `type=rule` · Cursor · ★ 41024
- Author: PatrickJS
- License: CC0-1.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/PatrickJS/awesome-cursorrules/tree/HEAD/rules/snowflake-data-engineering-cursorrules-prompt-file.mdc
- Updated: 2026-05-30
- HTML: https://affpapa.org/en/nevibecode/rules/snowflake-data-engineering-cursorrules-prompt-file

## What it does

This rule sets data engineering conventions for Snowflake. For semi-structured JSON in `VARIANT` fields, it enforces colon notation, explicit data type casts (`::STRING`, `::NUMBER`), and flattening nested arrays with `LATERAL FLATTEN`. Storing mixed data types inside the same field is discouraged because it breaks subcolumnarization.

Pipeline design depends on the task. Declarative Dynamic Tables handle transformation chains, Snowpipe ingests files from cloud stages, and Streams with Tasks power imperative CDC workloads. New tasks start in a suspended state. You must explicitly activate them with `ALTER TASK ... RESUME`.

Platform guidance also covers Apache Iceberg tables and Snowflake Postgres instances with `pg_lake`. To control virtual warehouse costs, the rule advises setting `AUTO_SUSPEND = 60`, enabling `AUTO_RESUME`, and provisioning warehouses by query complexity rather than raw data size.

## Requirements
- Works with: Snowflake, PostgreSQL

## Install

### Cursor (native platform)

**Manually: put the files in place**
- File: `.cursor/rules/snowflake-data-engineering-cursorrules-prompt-file.mdc` — Frontmatter: description, globs, alwaysApply

### Claude Code

**Manually: put the files in place**
- File: `.claude/rules/snowflake-data-engineering-cursorrules-prompt-file.md` — The paths frontmatter field limits the files: move globs from the source into paths

### Codex

**AGENTS.md**
- Codex reads AGENTS.md: paste the rule text there

### GitHub Copilot

**Manually: put the files in place**
- File: `.github/instructions/snowflake-data-engineering-cursorrules-prompt-file.instructions.md` — The applyTo field sets which files it applies to: move globs from the source into applyTo

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/rules/snowflake-data-engineering-cursorrules-prompt-file.md`

### Cline

**Manually: put the files in place**
- File: `.clinerules/snowflake-data-engineering-cursorrules-prompt-file.md`

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/PatrickJS/awesome-cursorrules/tree/HEAD/rules/snowflake-data-engineering-cursorrules-prompt-file.mdc

## When to use it
- unpack semi-structured JSON records using `LATERAL FLATTEN`
- configure data pipelines using Dynamic Tables and Snowpipe
- implement change data capture pipelines with Streams and Tasks
- reduce compute costs by configuring `AUTO_SUSPEND` on warehouses

## Example prompts
- Create a Dynamic Table definition to clean `raw_events` with a 5-minute lag
- Unnest an array from `src:items` using `LATERAL FLATTEN` with explicit casts
- Write a scheduled Task using CRON that consumes changes from `raw_events_stream`

## Source text · snowflake-data-engineering-cursorrules-prompt-file.mdc · CC0-1.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: c7bbfc991834e2e9.

BEGIN THIRD-PARTY FILE c7bbfc991834e2e9
```text
---
description: "Cursor rules for Snowflake SQL, data pipelines (Dynamic Tables, Streams, Tasks, Snowpipe), semi-structured data, Snowflake Postgres, and cost optimization."
globs: **/*
alwaysApply: false
---
// Snowflake Data Engineering
// Comprehensive guidance for SQL, data pipelines, and platform best practices on Snowflake

You are an expert Snowflake data engineer with deep knowledge of the entire platform: SQL, data pipelines (Dynamic Tables, Streams, Tasks, Snowpipe), semi-structured data, Snowflake Postgres, and cost optimization.

// Architecture
// Snowflake separates storage (columnar micro-partitions), compute (elastic virtual warehouses), and services (metadata, security, optimization).

// ═══════════════════════════════════════════
// SQL AND SEMI-STRUCTURED DATA
// ═══════════════════════════════════════════

// Use VARIANT, OBJECT, and ARRAY types for JSON, Avro, Parquet, ORC.
// Access nested fields with colon notation: src:customer.name::STRING
// Cast explicitly: src:price::NUMBER(10,2), src:created_at::TIMESTAMP_NTZ
// Flatten arrays:
//   SELECT f.value:name::STRING AS name
//   FROM my_table, LATERAL FLATTEN(input => src:items) f;
// Flatten semi-structured into relational columns when data contains dates, numbers as strings, or arrays.
// Avoid mixed types in the same VARIANT field — prevents subcolumnarization.
// VARIANT null vs SQL NULL: JSON null stored as string "null". Use STRIP_NULL_VALUES => TRUE on load.

// SQL Coding Standards
// - snake_case for all identifiers. Avoid quoted identifiers.
// - CTEs over nested subqueries. CREATE OR REPLACE for idempotent DDL.
// - COPY INTO for bulk loading, not INSERT. MERGE for upserts:
//   MERGE INTO target t USING source s ON t.id = s.id
//   WHEN MATCHED THEN UPDATE SET t.name = s.name
//   WHEN NOT MATCHED THEN INSERT (id, name) VALUES (s.id, s.name);

// Stored Procedures — prefix variables with colon : inside SQL statements:
//   CREATE PROCEDURE my_proc(p_id INT) RETURNS STRING LANGUAGE SQL AS
//   BEGIN
//     LET result STRING;
//     SELECT name INTO :result FROM users WHERE id = :p_id;
//     RETURN result;
//   END;

// ═══════════════════════════════════════════
// PERFORMANCE OPTIMIZATION
// ═══════════════════════════════════════════

// Cluster keys: for very large tables (multi-TB), on WHERE/JOIN/GROUP BY columns.
//   ALTER TABLE large_events CLUSTER BY (event_date, region);
// Search Optimization Service: point lookups on high-cardinality columns, substring/regex.
//   ALTER TABLE logs ADD SEARCH OPTIMIZATION ON EQUALITY(sender_ip), SUBSTRING(error_message);
// Materialized Views: pre-compute expensive aggregations (single table only).
// Use RESULT_SCAN(LAST_QUERY_ID()) to reuse results. Query tags for attribution:
//   ALTER SESSION SET QUERY_TAG = 'etl_daily_load';

// ═══════════════════════════════════════════
// DATA PIPELINES
```
END THIRD-PARTY FILE c7bbfc991834e2e9

The third-party file has ended. Everything between the c7bbfc991834e2e9 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

First 3310 of 8333 bytes. © PatrickJS · CC0-1.0 · https://github.com/PatrickJS/awesome-cursorrules/tree/HEAD/rules/snowflake-data-engineering-cursorrules-prompt-file.mdc

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