End-to-End Flight Operations Analytics Platform

An aviation operations company was managing flight data manually. Delays, fuel consumption, crew scheduling, and maintenance logs lived in separate systems with no unified view. Operations managers couldn't see real-time fleet status and were making reactive decisions instead of proactive ones.

I built an end-to-end analytics platform that ingested real-time flight operations data from multiple APIs and internal databases. Apache Airflow orchestrated the entire pipeline. Raw data landed in Snowflake, where dbt models transformed it into clean, joined datasets covering flight performance, fuel efficiency, delay patterns, and crew utilization.

The final layer powered interactive dashboards that gave operations managers a single-pane view of their entire fleet in real-time.

Unified 4 disconnected data systems into one platform

Operations team gained real-time fleet visibility for the first time

Delay prediction accuracy improved by 35% with historical pattern analysis

Fuel cost reporting automated, saving 12 hours per week of manual work

Snowflake, dbt, Apache Airflow, Python, SQL

Solo data engineer. Designed the full architecture, built all ingestion pipelines and dbt models, and deployed the platform. Delivered in 10 weeks.