IDR FX Advisor

A daily ELT pipeline that helps Indonesians decide when to exchange IDR to foreign currency, sending 5-level Discord signals (STRONG BUY → STRONG WAIT) based on percentile rank and multi-window z-score analysis. Built with Airflow, dbt, BigQuery, and Terraform.

A self-initiated data engineering project that turns a real personal problem — timing IDR-to-foreign-currency exchanges — into an automated, alert-driven pipeline on the modern data stack.

Airflow fetches daily rates from the Frankfurter API into BigQuery, dbt models compute a percentile rank over full history plus z-scores across 30/90/365-day windows to classify today's rate into a 5-level signal (STRONG BUY, BUY, NEUTRAL, WAIT, STRONG WAIT), and Airflow delivers it via Discord. The entire cloud infrastructure is defined as code with Terraform and runs locally in Docker.

What I built

Built an end-to-end ELT pipeline with Airflow orchestration, BigQuery warehousing, and version-controlled dbt transformations.
Engineered the signal in dbt using BigQuery window functions: a full-history percentile rank combined with 30/90/365-day z-scores, mapped to a 5-level STRONG BUY → STRONG WAIT recommendation.
Provisioned reproducible cloud infrastructure with Terraform and containerized the workflow with Docker.
Backfilled historical rates from 2021 and automated daily updates with Discord BUY/NEUTRAL/WAIT alerts.