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+---
+name: snowflake-development
+description: "Comprehensive Snowflake development assistant covering SQL best practices, data pipeline design (Dynamic Tables, Streams, Tasks, Snowpipe), Cortex AI functions, Cortex Agents, Snowpark Python, dbt integration, performance tuning, and security hardening."
+category: data-engineering
+risk: safe
+source: community
+date_added: "2026-03-24"
+---
+
+# Snowflake Development
+
+You are a Snowflake development expert. Apply these rules when writing SQL, building data pipelines, using Cortex AI, or working with Snowpark Python on Snowflake.
+
+## SQL Best Practices
+
+### Naming and Style
+
+- Use `snake_case` for all identifiers. Avoid double-quoted identifiers — they create case-sensitive names requiring 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).
+
+### 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 raises "invalid identifier" errors.
+
+BAD:
+```sql
+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;
+```
+
+GOOD:
+```sql
+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;
+```
+
+### Semi-Structured Data
+
+- VARIANT, OBJECT, ARRAY for JSON/Avro/Parquet/ORC.
+- Access nested fields: `src:customer.name::STRING`. Always cast: `src:price::NUMBER(10,2)`.
+- VARIANT null vs SQL NULL: JSON `null` is stored as `"null"`. Use `STRIP_NULL_VALUE = TRUE` on load.
+- Flatten arrays: `SELECT f.value:name::STRING FROM my_table, LATERAL FLATTEN(input => src:items) f;`
+
+### MERGE for Upserts
+
+```sql
+MERGE INTO target t USING source s ON t.id = s.id
+WHEN MATCHED THEN UPDATE SET t.name = s.name, t.updated_at = CURRENT_TIMESTAMP()
+WHEN NOT MATCHED THEN INSERT (id, name, updated_at) VALUES (s.id, s.name, CURRENT_TIMESTAMP());
+```
+
+## Data Pipelines
+
+### Choosing Your Approach
+
+| Approach | When to Use |
+|----------|-------------|
+| Dynamic Tables | Declarative transformations. **Default choice.** Define the query, Snowflake handles refresh. |
+| Streams + Tasks | Imperative CDC. Use for procedural logic, stored procedure calls. |
+| Snowpipe | Continuous file loading from S3/GCS/Azure. |
+
+### Dynamic Tables
+
+```sql
+CREATE OR REPLACE DYNAMIC TABLE cleaned_events
+    TARGET_LAG = '5 minutes'
+    WAREHOUSE = transform_wh
+    AS
+    SELECT event_id, event_type, user_id, event_timestamp
+    FROM raw_events
+    WHERE event_type IS NOT NULL;
+```
+
+Key rules:
+- Set `TARGET_LAG` progressively: tighter at top, looser at bottom.
+- Incremental DTs **cannot** depend on Full refresh DTs.
+- `SELECT *` breaks on schema changes — use explicit column lists.
+- Change tracking must stay enabled on base tables.
+- Views cannot sit between two Dynamic Tables.
+
+### Streams and Tasks
+
+```sql
+CREATE OR REPLACE STREAM raw_stream ON TABLE raw_events;
+
+CREATE OR REPLACE TASK process_events
+    WAREHOUSE = transform_wh
+    SCHEDULE = 'USING CRON 0 */1 * * * America/Los_Angeles'
+    WHEN SYSTEM$STREAM_HAS_DATA('raw_stream')
+    AS INSERT INTO cleaned_events SELECT ... FROM raw_stream;
+
+-- Tasks start SUSPENDED — you MUST resume them
+ALTER TASK process_events RESUME;
+```
+
+## Cortex AI
+
+### Function Reference
+
+| Function | Purpose |
+|----------|---------|
+| `AI_COMPLETE` | LLM completion (text, images, documents) |
+| `AI_CLASSIFY` | Classify into categories (up to 500 labels) |
+| `AI_FILTER` | Boolean filter on text/images |
+| `AI_EXTRACT` | Structured extraction from text/images/documents |
+| `AI_SENTIMENT` | Sentiment score (-1 to 1) |
+| `AI_PARSE_DOCUMENT` | OCR or layout extraction |
+| `AI_REDACT` | PII removal |
+
+**Deprecated (do NOT use):** `COMPLETE`, `CLASSIFY_TEXT`, `EXTRACT_ANSWER`, `PARSE_DOCUMENT`, `SUMMARIZE`, `TRANSLATE`, `SENTIMENT`, `EMBED_TEXT_768`.
+
+### TO_FILE — Common Error Source
+
+Stage path and filename are **SEPARATE** arguments:
+
+```sql
+-- BAD: TO_FILE('@stage/file.pdf')
+-- GOOD:
+TO_FILE('@db.schema.mystage', 'invoice.pdf')
+```
+
+### Use AI_CLASSIFY for Classification (Not AI_COMPLETE)
+
+```sql
+SELECT AI_CLASSIFY(ticket_text,
+    ['billing', 'technical', 'account']):labels[0]::VARCHAR AS category
+FROM tickets;
+```
+
+### Cortex Agents
+
+```sql
+CREATE OR REPLACE AGENT my_db.my_schema.sales_agent
+FROM SPECIFICATION $spec$
+{
+    "models": {"orchestration": "auto"},
+    "instructions": {
+        "orchestration": "You are SalesBot...",
+        "response": "Be concise."
+    },
+    "tools": [{"tool_spec": {"type": "cortex_analyst_text_to_sql", "name": "Sales", "description": "Queries sales..."}}],
+    "tool_resources": {"Sales": {"semantic_model_file": "@stage/model.yaml"}}
+}
+$spec$;
+```
+
+Agent rules:
+- Use `$spec$` delimiter (not `$$`).
+- `models` must be an object, not an array.
+- `tool_resources` is a separate top-level object, not nested inside tools.
+- Do NOT include empty/null values in edit specs — clears existing values.
+- Tool descriptions are the #1 quality factor.
+- Never modify production agents directly — clone first.
+
+## Snowpark Python
+
+```python
+from snowflake.snowpark import Session
+import os
+
+session = Session.builder.configs({
+    "account": os.environ["SNOWFLAKE_ACCOUNT"],
+    "user": os.environ["SNOWFLAKE_USER"],
+    "password": os.environ["SNOWFLAKE_PASSWORD"],
+    "role": "my_role", "warehouse": "my_wh",
+    "database": "my_db", "schema": "my_schema"
+}).create()
+```
+
+- Never hardcode credentials.
+- DataFrames are lazy — executed on `collect()`/`show()`.
+- Do NOT use `collect()` on large DataFrames — process server-side.
+- Use **vectorized UDFs** (10-100x faster) for batch/ML workloads instead of scalar UDFs.
+
+## dbt on Snowflake
+
+Dynamic table materialization (streaming/near-real-time marts):
+```sql
+{{ config(materialized='dynamic_table', snowflake_warehouse='transforming', target_lag='1 hour') }}
+```
+
+Incremental materialization (large fact tables):
+```sql
+{{ config(materialized='incremental', unique_key='event_id') }}
+```
+
+Snowflake-specific configs (combine with any materialization):
+```sql
+{{ config(transient=true, copy_grants=true, query_tag='team_daily') }}
+```
+
+- Do NOT use `{{ this }}` without `{% if is_incremental() %}` guard.
+- Use `dynamic_table` materialization for streaming/near-real-time marts.
+
+## Performance
+
+- **Cluster keys**: Only multi-TB tables, on WHERE/JOIN/GROUP BY columns.
+- **Search Optimization**: `ALTER TABLE t ADD SEARCH OPTIMIZATION ON EQUALITY(col);`
+- **Warehouse sizing**: Start X-Small, scale up. `AUTO_SUSPEND = 60`, `AUTO_RESUME = TRUE`.
+- **Separate warehouses** per workload.
+- Estimate AI costs first: `SELECT SUM(AI_COUNT_TOKENS('claude-4-sonnet', text)) FROM table;`
+
+## Security
+
+- Follow least-privilege RBAC. Use database roles for object-level grants.
+- Audit ACCOUNTADMIN regularly: `SHOW GRANTS OF ROLE ACCOUNTADMIN;`
+- Use network policies for IP allowlisting.
+- Use masking policies for PII columns and row access policies for multi-tenant isolation.
+
+## Common Error Patterns
+
+| Error | Cause | Fix |
+|-------|-------|-----|
+| "Object does not exist" | Wrong context or missing grants | Fully qualify names, check grants |
+| "Invalid identifier" in proc | Missing colon prefix | Use `:variable_name` |
+| "Numeric value not recognized" | VARIANT not cast | `src:field::NUMBER(10,2)` |
+| Task not running | Forgot to resume | `ALTER TASK ... RESUME` |
+| DT refresh failing | Schema change or tracking disabled | Use explicit columns, check change tracking |