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Security · Version 1.6.0 · Reviewed 2026-08-02

Data Retention Policy Engineer

Find and prioritize exploitable risk in retention control mapping and deletion workflow design with evidence, explicit trade-offs, and a verification plan.

4 method steps 5 documented failure modes 5 diagnostic checks 7 quality gates

Translates retention requirements into store-level deletion, legal hold, backup expiry, derived-data handling, evidence, and ownership.

₹99 one-time

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What this skill helps you do

  • Retention control mapping
  • Deletion workflow design
  • Backup-expiry verification

How Data Retention Policy Engineer works

You provide

Obligations, data inventory, and current controls

It inspects

Requirement type and implemented control for retention control mapping

It decides

A deletion workflow design gap register with accountable owners

You verify

Each control mapped to evidence an auditor would accept

What it checks first

Data Retention Policy Engineer translates retention requirements into store-level deletion, legal hold, backup expiry, derived-data handling, evidence, and ownership. Use it when the work involves Retention control mapping, Deletion workflow design, Backup-expiry verification.

  1. Whether the obligation is a legal requirement, a contractual commitment, or an internal policy — the escalation path differs.
  2. The specific data categories and lawful basis, rather than a general statement about compliance.
  3. Data flows across jurisdictions and processors, which determine transfer obligations.
  4. Retention and deletion behavior in every downstream copy, including backups and analytics.
  5. Who is accountable for the decision, since a compliance analysis without an owner is not actionable.

Failure modes it recognizes

  • Deletion implemented in the primary store while copies persist in backups, exports, logs, and warehouses.
  • Consent collected for one purpose and reused for another without a valid basis.
  • A subprocessor added without a data-processing agreement or customer notification.
  • Retention policy defined but never enforced by an automated job.
  • A control documented in policy but not implemented in the system it describes.

Answers it will reject

  • Providing a definitive legal conclusion rather than a structured analysis for qualified review.
  • Treating a compliance certification as evidence that a specific control works.
  • Relying on contractual language to mitigate a technical risk that is technically preventable.
  • Presenting risk without severity, likelihood, and the accountable owner.

Decision rules it applies

  • Separate legal requirement, contractual obligation, and internal policy in every finding.
  • Escalate to qualified counsel for anything that constitutes legal advice, and say so plainly.
  • Map every obligation to a specific implemented control and its evidence, or mark it as a gap.
  • Prefer technical enforcement over documented intent, because documented intent is not a control.

Evidence it asks for

  • Build a data inventory: category, source, purpose, basis, location, retention, and downstream copies.
  • Trace one deletion request end to end and enumerate every store it must reach.
  • Record the evidence artifact that would satisfy an auditor for each control.

The method inside

  1. Establish what is actually true about retention control mapping from the supplied evidence, and mark what is missing.
  2. Identify the mechanism behind deletion workflow design rather than restating the symptom.
  3. Choose the smallest defensible change for backup-expiry verification, weighing impact, confidence, effort, and reversibility.
  4. Recommend defense-in-depth and verification

Deliverables

  • Retention control mapping assessment
  • Deletion workflow design decision and action plan
  • Backup-expiry verification verification checklist

Evidence requirements

  • Code, configuration, data flows, and trust boundaries
  • Identity, authorization, and deployment context
  • Threat model, controls, and known assumptions

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

Design technical controls to delete customer data after thirty days across our database, search index, object store, and backups.

Expected output

Create one deletion manifest keyed by customer identity, execute store-specific deletion idempotently, track derived indexes, and document backup expiry separately because immutable backups cannot be selectively rewritten...

Boundaries and compatibility

Ideal for

  • Retention control mapping: produce a decision or artifact grounded in supplied evidence.
  • Deletion workflow design: produce a decision or artifact grounded in supplied evidence.
  • Backup-expiry verification: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Authorizing offensive actions against systems without permission
  • Reporting theoretical issues as exploitable without a path

Agent compatibility

  • GitHub Copilot custom agents
  • Claude Agent Skills / SKILL.md
  • Any instruction-following chat model

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.