Use when writing Snowflake SQL, building data pipelines with Dynamic Tables or Streams/Tasks, using Cortex AI functions, creating Cortex Agents, writing Snowpark Python, configuring dbt for Snowflake, or troubleshooting Snowflake errors.
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Use when writing Snowflake SQL, building data pipelines with Dynamic Tables or Streams/Tasks, using Cortex AI functions, creating Cortex Agents, writing Snowpark Python, configuring dbt for Snowflake, or troubleshooting Snowflake errors.
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LanguagePython
LicenseMIT
📦 Ships with claude-skills
</> SKILL.md
snowflake-development.SKILL.md
---name: "snowflake-development"
description: "Use when writing Snowflake SQL, building data pipelines with Dynamic Tables or Streams/Tasks, using Cortex AI functions, creating Cortex Agents, writing Snowpark Python, configuring dbt for Snowflake, or troubleshooting Snowflake errors."
---# Snowflake Development
Snowflake SQL, data pipelines, Cortex AI, and Snowpark Python development. Covers the colon-prefix rule, semi-structured data, MERGE upserts, Dynamic Tables, Streams+Tasks, Cortex AI functions, agent specs, performance tuning, and security hardening.
> Originally contributed by [James Cha-Earley](https://github.com/jamescha-earley) — enhanced and integrated by the claude-skills team.
## Quick Start
```bash
# Generate a MERGE upsert template
python scripts/snowflake_query_helper.py merge --target customers --source staging_customers --key customer_id --columns name,email,updated_at
# Generate a Dynamic Table template
python scripts/snowflake_query_helper.py dynamic-table --name cleaned_events --warehouse transform_wh --lag "5 minutes"
# Generate RBAC grant statements
python scripts/snowflake_query_helper.py grant --role analyst_role --database analytics --schemas public,staging --privileges SELECT,USAGE
```
---## SQL Best Practices
### Naming and Style
- Use `snake_case` for all identifiers. Avoid double-quoted identifiers -- they force case-sensitive names that require constant quoting.
- Use CTEs (`WITH` clauses) over nested subqueries.
- Use `CREATE OR REPLACE` for idempotent DDL.
- Use explicit column lists -- never `SELECT *` in production. Snowflake's columnar storage scans only referenced columns, so explicit lists reduce I/O.
### Stored Procedures -- Colon Prefix Rule
In SQL stored procedures (BEGIN...END blocks), variables and parameters **must** use the colon `:` prefix inside SQL statements. Without it, Snowflake treats them as column identifiers and raises "invalid identifier" errors.
```sql
-- WRONG: missing colon prefix
SELECT name INTO result FROM users WHERE id = p_id;
-- CORRECT: colon prefix on both variable and parameter
SELECT name INTO :result FROM users WHERE id = :p_id;
```
This applies to DECLARE variables, LET variables, and procedure parameters when used inside SELECT, INSERT, UPDATE, DELETE, or MERGE.
### Semi-Structured Data
- VARIANT, OBJECT, ARRAY for JSON/Avro/Parquet/ORC.
- Access nested fields: `src:customer.name::STRING`. Always cast with `::TYPE`.
- VARIANT null vs SQL NULL: JSON `null` is stored as the string `"null"`. Use `STRIP_NULL_VALUE = TRUE` on load.
4. **Consult troubleshooting reference**: See `references/troubleshooting.md` for error-specific fixes
---
## Anti-Patterns
| Anti-Pattern | Why It Fails | Better Approach |
|---|---|---|
| `SELECT *` in Dynamic Tables | Schema changes upstream break the DT silently | Use explicit column lists |
| Missing colon prefix in procedures | "Invalid identifier" runtime error | Always use `:variable_name` in SQL blocks |
| Single warehouse for all workloads | Contention between load, transform, and query | Separate warehouses per workload type |
| Hardcoded credentials in Snowpark | Security risk, breaks in CI/CD | Use `os.environ[]` or key pair auth |
| `collect()` on large DataFrames | Pulls entire result set to client memory | Process server-side with DataFrame operations |
| Nested subqueries instead of CTEs | Unreadable, hard to debug, Snowflake optimizes CTEs better | Use `WITH` clauses |
| Using deprecated Cortex functions | `CLASSIFY_TEXT`, `SUMMARIZE` etc. will be removed | Use `AI_CLASSIFY`, `AI_COMPLETE` etc. |
| Tasks without `WHEN SYSTEM$STREAM_HAS_DATA` | Task runs on schedule even with no new data, wasting credits | Add the WHEN clause for stream-driven tasks |
| Double-quoted identifiers | Forces case-sensitive names across all queries | Use `snake_case` unquoted identifiers |
---
## Cross-References
| Skill | Relationship |
|-------|-------------|
| `engineering/sql-database-assistant` | General SQL patterns — use for non-Snowflake databases |
| `engineering/database-designer` | Schema design — use for data modeling before Snowflake implementation |
| `engineering-team/senior-data-engineer` | Broader data engineering — pipelines, Spark, Airflow, data quality |
| `engineering-team/senior-data-scientist` | Analytics and ML — use alongside Snowpark for feature engineering |
