- Define which ETL/ELT platforms are in scope (PowerCenter, IDMC, ADF, Glue, Databricks, SSIS, Talend, DBT).
- Specify environments covered (Dev, Test, UAT, Prod).
- State the data domains or project areas included.
2. Engineering Standards & Coding Guidelines
- Vendors must follow documented design and code conventions.
- All pipelines must use approved naming, foldering, and design patterns.
- Rules around performance, maintainability, and housekeeping must be followed.
3. Objective Code Quality Metrics
- Minimum rule adherence: 95% pass rate across all checks.
- High-severity issues: 0 allowed in production code.
- Medium severity: Must be reviewed and remediated within defined timelines.
- Waiver requests must include justification and approval workflow.
- Automated analysis must be run on every pull request or code drop.
- High-severity defects: fix within 3 business days.
- Medium severity: fix within 10 business days.
- Low severity: address during sprint cleanup or refactor cycles.
5. Documentation & Knowledge Transfer
- Every pipeline must include design notes and business rule documentation.
- Vendors must provide a handover plan at project completion.
- Reusable components must be cataloged and documented.
6. Reporting & Transparency
- Weekly or sprint-based reporting of quality scores and open issues.
- Access to dashboards (manual or automated) is required.
- Audit-ready evidence must be provided upon request.
A consistent SLA prevents quality regressions and creates a shared understanding between internal teams and vendors. With automated enforcement, deviations from standards become visible immediately—not months later during production outages.