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Idrees Kamal
Open to applied AI roles
All work

Reliable employee data. Controlled changes.

An HR lifecycle integration built around identity, exceptions, and verification.

JDA TSG · 2026 · Production integration

At a glance

The four lifecycle paths
Status
Production integration
Stack
Make · REST APIs · Lifecycle routing · Canary testing · Reconciliation
Evidence
Production workflow, controlled test results, and destination readbacks. Internal artifacts are confidential; architecture is summarized here.

The problem

Employee lifecycle changes needed to move reliably between HR and performance systems. File-based handoffs and mismatched identities created correction work and operational risk.

My role

I led the integration work: lifecycle routing, identity matching, source write-backs, exception handling, test design, controlled correction waves, and destination verification.

Decisions that mattered

  1. 01Treat create, update, deactivate, and reactivate as distinct paths with explicit matching rules.
  2. 02Test a small canary before expanding a change; define rollback and exception ownership before execution.
  3. 03Read the destination API after a change. A successful request alone is not proof of the intended record state.

What changed

Delivered the core production sync and verified corrections across hundreds of employee records. Correction cohorts overlap and are not added together.

Walkthrough

Sample record · EMP-1042Receive the change

A fictional employee record arrives with a department change.

ProceedingOperations → Client Services
Fictional record · no live system calls

Follow one employee change.

What this establishes

This describes delivered capability and verified corrections, not quantified labor savings or a claim that every reconciliation exception was closed.

What I would measure next

Measure correction frequency, exception aging, and handling time against a pre-change baseline.

Contact

Want a walkthrough of this work?

Email me ikamal97@gmail.com