Guillermo Rodríguez Jover

Designed an always-running marketing data analytics tool for a mobile loyalty app with +70 million registered users and +10 million weekly active users.

Defined strategic KPIs and business goals. Implemented ETL and data warehouse using Spark on Azure Databricks for daily ingest of data orchestrated with Apache Airflow on Kubernetes. Reported results and explored data assets. Shared insights and guidance in marketing campaign definition for +25 countries.

Conceptualized and implemented an automation and intelligent solution to control and adjust over 3,000 orders per day for a first-level FMCG client. There were over 1,000 SKUs previously done manually by a team of ten people.

As a result, there was a cutoff of 35-40% in human capital costs, saving 50,000€ per year once the solution was fully implemented.

I designed it using Python and Airflow to orchestrate the jobs. The tool did not need human intervention. The main challenge during the solution's lifecycle was to move from on-premises infrastructure to cloud base services in Azure. By accomplishing this, there was a reduction of over 50% in maintenance expenses.

The client and I uncovered a drop in operational margin by up to 50% due to the massive amount of time spent filling reports for equipment maintenance.

The workflow for the maintenance checklist was manual, time-consuming, and suboptimal. To streamline the process and increase the productivity and profitability of the projects, I created a web app based on Django, PostgreSQL, Docker, and Azure.

As a result, a quarter after the implementation of the tool was finished, the customer reduced the time spent filling in the forms by 30-40% and increased the profit margin of the projects by 7-15%.