Membership validation and data quality

This work ran in member portals where users had to validate themselves with their credentials, then update profile data before accessing services or purchase flows.

Legacy data was inconsistent and unreliable. Postal codes and municipalities didn't match, country fields came in several different formats, and the forms had accumulated years of un-normalized values.

Users were getting blocked at login and update because identity and profile fields were often wrong at the source, so the portal had to distinguish between invalid credentials, malformed input and recoverable data issues.

The flow had to validate against the LALIGA member-management platform's API and push corrected data to the CRM Data Lake, so accepting broken input to clean later wasn't an option.

I designed login, registration, and mandatory profile update flows with validation on both frontend and backend, including credentials checks before the user could move deeper into the portal.

For normalization, I used explicit rules plus JSON mappings to verify postal code and municipality pairs, and added server-side validation, duplicate controls, indexes, and database restrictions before persisting and forwarding data.

The portals stopped accepting inconsistent profile data as-is and started enforcing normalized updates before users continued.

That reduced blocked users caused by malformed identity and profile input, and lowered the amount of mismatched records reaching the Data Lake and downstream operational flows.

The trade-off is that the portal now blocks users with malformed legacy records until they update — we kept the path recoverable, but it added friction for accounts that hadn't been touched in years.