During a technical interview, a Google Developer Expert in Data Analytics reviewed the Bitcoin Cash data platform I had built for a Data Engineer take-home challenge.

The project used Terraform, BigQuery, dbt Core, and GitHub Actions.

It was also my first time using Terraform.

The review was positive.

The reviewer especially appreciated how I had used AI. I did not let it complete the project for me. I used it to move faster through unfamiliar tools, then went back through the code, logs, and architecture until I could explain what most parts were doing.

Most parts.

When I was asked why I had configured the BigQuery permissions in a specific way, I could explain what the roles allowed, but not why I had chosen them.

The honest answer was simple:

I had let the AI decide.

The reviewer explained that BigQuery separates compute from storage.

A service account needs permission to create query jobs, but it also needs permission to read or modify the relevant datasets.

The configuration worked.

My understanding arrived later.

We also discussed Terraform.

I knew how to use plan to preview changes and apply to deploy them, but my state file was still stored locally.

That may be acceptable for a small personal project, but not for a team. Shared infrastructure state should usually live in a secured remote backend so it does not depend on one person’s machine.

He recommended that I learn more about Terraform’s plan, state, and apply lifecycle, as well as dbt Cloud and its configuration system.

The most useful part of the interview was not the technical correction.

It was the direction it gave me.

The engineers I spoke with were able to move between data analysis and data engineering depending on the problem.

That is the kind of profile I want to build.

My long-term goal is to become a data project manager, but I do not want to reach that role only knowing how to manage deadlines and meetings.

I want practical experience in analysis, engineering, infrastructure, and delivery.

I want to understand the work before I am responsible for leading it.

This project showed me that AI can help me enter unfamiliar technical territory quickly.

The review reminded me that a working system is only the beginning.

The next step is being able to explain every decision inside it.