Stakeholder Sign Off Process

Who this is for

ETL Developers, Data Engineers, and Analytics Engineers who deliver data pipelines, tables, or jobs that need formal approval from business and technical stakeholders before go-live.

Prerequisites

• Basic ETL pipeline knowledge (sources, transforms, targets)
• Familiarity with version control and tagging releases
• Ability to read requirements and define acceptance criteria
• Comfort with tickets, change requests, and simple runbooks

Why this matters

Sign-off is your safety net. It clarifies what “done” means, who approves, and what happens if things go wrong. In real projects, missing sign-off leads to scope creep, ownership disputes, and post-release fire drills. A clean sign-off process saves time and protects you and your team.

• Typical tasks: prepare sign-off packet, schedule review, demonstrate results, document approvals, baseline the release, and hand over.
• Typical outcomes: clear acceptance criteria met, names and timestamps of approvers recorded, version is baselined, rollback ready.

Concept explained simply

Stakeholder sign-off is the structured moment where you show the result, map it to agreed criteria, and get written approval to release or proceed.

Mental model: Define → Show → Decide → Record → Freeze

1. Define: measurable acceptance criteria and who must approve.
2. Show: demo evidence (queries, dashboards, logs, QA results).
3. Decide: approve, approve with conditions, or reject with fixes.
4. Record: outcomes, names, time, and any follow-ups.
5. Freeze: baseline the approved version and hand over.

1. Data completeness: ≥ 99.8% rows vs source for last 30 days
2. Freshness: daily load finishes by 06:30 UTC on weekdays
3. Accuracy: revenue variance vs source ≤ 0.1%
4. Schema: final table has columns [id, date, revenue, channel] with documented types
5. Observability: alerts on late loads and >0.1% variance configured
6. Access: BI group has read-only access; PII masked per policy

Requester (Business): Accountable (A)
Data Owner (Source): Consulted (C)
ETL Developer: Responsible (R)
Data Architect: Consulted (C)
QA / Data Quality: Responsible (R)
Security/Compliance: Consulted (C) if PII
Product/BI Lead: Approver (A)
Platform/Operations: Informed (I)

Version: v1.4.0
Ticket(s): DE-1234, DE-1251
Scope: New dim_channel; modified revenue calc
Out of scope: historical backfill prior to 2021
Known risks: upstream API rate limits
Rollback plan: revert to v1.3.2; disable job schedule

1. Objective and scope (2 min)
2. Acceptance criteria recap (2 min)
3. Evidence demo (8 min)
4. Risks & rollback (3 min)
5. Decision & next steps (5 min)

Step-by-step process

1. Identify approvers early
   Name actual people who must say yes. If PII or cost impacts exist, include Security/Finance. Avoid “team X approves.”
2. Draft acceptance criteria
   Make them measurable and testable. Tie each to evidence you can show.
3. Prepare the sign-off packet
   Include scope, criteria, evidence screenshots/queries, change log, risks, rollback, and the sign-off matrix.
4. Run the review
   Walk through agenda, show results, capture questions and decisions in the same document.
5. Record approvals
   Get explicit “Approved by Name, Role, Date/Time.” If conditions exist, list them and who owns them.
6. Baseline and hand over
   Tag the repo/release, update runbook, enable schedules, notify support channels, and archive the packet.

Worked examples

Example 1: New Marketing Attribution Table

Context: New table marketing.attribution_daily feeding dashboards. PII hashed. Freshness SLA 07:00 UTC.

• Criteria: completeness ≥ 99.5%, SLA met 5 consecutive days in pre-prod, PII hashed, schema documented.
• Approvers: Marketing Analytics Lead (A), Data Architect (C), Security (C for PII), ETL Dev (R).
• Evidence: query counts vs source, scheduler run history, masking tests.
• Outcome: Approved with condition to raise alert on >0.5% drop in completeness. Owner: ETL Dev. Due: before prod enable.
• Baseline: tag v0.9.0, enable prod schedule, archive packet.

Example 2: Finance Bug Fix Patch

Context: Fix rounding error in revenue. High risk for finance reporting mid-quarter.

• Criteria: historical variance ≤ 0.05% on last 90 days; no late jobs; sign-off required from Finance Controller.
• Approvers: Finance Controller (A), Data Engineer (R), QA (R).
• Evidence: side-by-side variance sheet, job run logs, rollback plan to previous tag.
• Outcome: Approved. Scheduled after business hours with monitoring.
• Baseline: tag v1.3.2 → v1.3.3; runbook updated.

Example 3: Source Schema Change

Context: Upstream API adds optional field country_code. Need to pass-through with nulls allowed.

• Criteria: pipeline resilience when field absent; downstream not breaking; documentation updated.
• Approvers: Data Owner (A), BI Lead (A), Architect (C).
• Evidence: test runs with and without field; contract test; downstream query checks.
• Outcome: Approved with time-boxed monitoring (2 weeks) and alert thresholds.
• Baseline: tag v2.0.0 (backward-compatible contract noted).

Common mistakes and how to self-check

• Vague criteria: “Looks good” is not measurable. Replace with thresholds and timestamps.
• Missing approver names: “Finance to approve.” Who exactly? Add names and backup approvers.
• No rollback: Even small changes need a revert tag and disable plan.
• Out-of-scope not stated: Prevent scope creep by listing what is not included now.
• No evidence: Always attach queries, screenshots, or logs tied to each criterion.

Exercises

Note: Everyone can do the exercises and the quick test. If you are logged in, your progress will be saved.

Exercise 1: Build a Sign-off Matrix and Criteria

Create a sign-off plan for a new dim_customer table that joins CRM and orders. Include PII masking, daily freshness, and a 0.2% accuracy threshold vs source.

Exercise 2: Draft the Approval Record

Write the approval note (as if in a ticket comment) capturing decision, any conditions, owners, and due dates.

Practical projects

• Prepare a sign-off packet for a small pipeline (CSV → staging → curated table). Run a mock review with a teammate acting as the approver.
• Create a reusable sign-off template in your team repo: criteria, matrix, agenda, change log, and approval record section.
• Set up a dry-run rollback for a tagged release and document the exact commands and steps.

Learning path

• Before this: Requirements gathering, data quality checks, runbooks.
• This topic: Stakeholder identification, measurable criteria, approval records, baselining.
• After this: Release notes, support handover, post-release monitoring, and change management.

Mini challenge

In one page, capture scope, three must-have criteria, two risks with mitigations, named approvers, and the exact command/tag to roll back. Keep it clear enough that a new joiner could execute it tomorrow.

Next steps

• Use the templates above on your next change request.
• Run the quick test below to reinforce key points.
• Schedule a 15-minute dry-run of your sign-off review with a peer.