AI Data Retention Policy Enforcement Developer

Wolvex Cloud

Remote · $100k – $130k / year · Full-time · Posted 4 months ago

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About the role

Data retention policies specify how long different categories of data should be kept before deletion or archival. Under GDPR, CCPA, HIPAA, and various sector-specific regulations, these aren't optional — they're legal obligations. An organization that retains customer data longer than its stated retention period, or that retains regulated data beyond statutory limits, faces regulatory exposure every day the data persists. Manual enforcement of retention policies across distributed data estates doesn't scale. We serve 40 European enterprise clients with data governance and privacy compliance automation. Data retention policy enforcement is the workflow complement to our erasure automation: where erasure handles individual subject requests, retention enforcement handles the systematic deletion of data that has aged past its retention period across the full data estate. You'll build the retention policy enforcement system: cataloging data assets with their retention classification, implementing age-based deletion scheduling that identifies and queues expired data for deletion, building the retention audit trail that demonstrates regulatory compliance, and handling the edge cases where data subject to legal hold should be preserved beyond its normal retention period.

Fully remote.

Responsibilities

Build data asset classification mapping datasets and tables to their applicable retention policy categories
Implement age-based deletion scheduling identifying data that has exceeded retention period across the data estate
Develop legal hold management preserving data beyond retention period when litigation hold applies
Create retention compliance audit trail documenting scheduled and completed deletion events for regulatory review
Build retention policy change impact analysis when policy periods are updated or regulatory requirements change
Monitor retention SLA tracking the lag between data reaching retention age and confirmed deletion completion

Requirements

3+ years in data engineering or platform engineering with GDPR, data governance, or retention policy implementation experience
Strong Python and SQL skills with scheduled workflow automation and audit trail generation
Understanding of GDPR retention principles, legal hold requirements, and data classification taxonomy
Experience building data lifecycle automation that integrates with regulatory audit processes
Ability to handle edge cases in retention policy logic without introducing accidental data deletion