Ashans
Khadka

I saved $376K annually by replacing a compliance vendor with an in-house deletion API.

Regulatory deletion reaches into every store that holds customer data. A request is not done until we can verify its result across those systems. The existing vendor workflow was expensive and put a core legal obligation outside our control, so I built the in-house replacement.

The requirements kept changing as new stores and retention rules arrived. I separated the business rules from the storage layer, which meant we could adapt the underlying systems without rewriting the core logic. The rate-limited GDPR/CCPA services now run in every production environment, process approximately 200K PII-based requests per month, preserve data residency, and protect production performance.

What I'd do differently: I would define, validate, and version the data contract on day one. The first version relied too much on one system's document shape, which made later changes harder to reason about.

Cutting MongoDB upgrade cycles from months to weeks across seven environments.

I led the 4.4 through 8.0 upgrades. Database upgrades have enough ways to fail without discovering one during the change, so I used maintenance windows, standby-cluster safety nets, and rollback paths we had tested before relying on them.

I also wrote reusable runbooks and brought teammates into the work so upgrades could move faster without becoming less safe.

Catching CDC failures before they become incidents.

A dashboard can look healthy while a data pipeline is still missing records. I built continuous validation that compared change events with landing data so we could see whether the path was actually complete.

It caught five pre-incident issues, including schema-driven lakehouse gaps, source-database ingestion delays, MSK throttling, and oversized events rejected by MSK. I presented the result to the wider engineering organization.