Production systems

Membership validation and data quality

Validation flows integrated with LALIGA and Data Lake.

Normalized legacy data and enforced validation at entry points to prevent inconsistencies across systems.

Role

Software Engineer / Integration Owner

Type

Production systems

Context

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

Problem

Problem and constraints

Legacy data was inconsistent and unreliable: mismatched postal codes, duplicated formats, and years of unvalidated input.

Users were frequently blocked due to incorrect identity and profile data, requiring the system to distinguish between invalid credentials and recoverable data issues.

The system had to validate against LALIGA APIs and push clean data downstream, making it impossible to defer corrections.

Approach

Approach and technical decisions

I designed login, registration, and mandatory profile update flows with validation on both frontend and backend, including idPersona and PIN 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.

Challenges

Supporting broken legacy formats without turning the user flow into a dead end.

Making data correction mandatory at the portal entry point while keeping the path recoverable.

Aligning validation rules, DB constraints, and downstream Data Lake requirements in the same flow.

Outcome

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.