skills/implement-data-code/SKILL.md

---
name: implement-data-code
description: Improve SQL, Spark, ETL/ELT, CDC and pipeline implementation code while preserving data grain, keys, correctness and replay safety.
---

# Implement Data Code

Use this skill only for its stated purpose. Follow the shared source-of-truth, permission and evidence rules in `../../references/workflow-contract.md`. Read `../../references/data-code-contracts.md` for detailed method when necessary.

## Procedure
1. Map source/output grain, keys, joins, null handling, ordering, schema and downstream consumers.
2. Check duplicates, CDC merges, retry/idempotence, replay windows and late/deleted events.
3. Implement minimal transformation or pipeline fix; avoid DISTINCT as a band-aid.
4. Add representative quality and reconciliation tests including repeat/replay cases.
5. Profile for tuning only after outputs are proven correct.
For full data-platform incident programs, advise appropriate specialized scope rather than overstating this coding skill.

## Handoff rule
State actual artifacts or grounded code findings and validation status. Never invent file paths, executed tests, tool access, or completed subagent work. Keep output proportionate to the user request.