Jesús Adraz | Data Engineer

Jesús Adraz

Data Engineer

Based in Caracas, VE

About

Data Analyst with over 3 years of professional experience working in the digital transformation of several companies in different fields, including a Buy Now Pay Later company, pharmaceutical distributors, convenience stores, and supermarkets. Implementing Odoo ERP with an analytical and improvement-oriented approach to business decision-making through data. Proficient in using SQL and GCP to manage and clean data. Looker Studio for creating dashboards and Python to automate processes, clean, visualize, and web scraping data. I have successfully implemented BI projects based on metrics that improved company decision-making.

Skills

Projects

Intelifarma Web Application

Web application focused on the use of data as a mechanism to drive the growth of the pharmaceutical retail sector in Venezuela, through a web application that provides simple, effective, and low-cost tools for all pharmacies that want to be part of the country's smart pharmacy ecosystem.

COVID-19 Dashboard

I used a dataset from Kaggle about COVID-19 novel around the world. I did some data cleaning with pandas to extract data from Germany and Venezuela. Then, I created a dashboard using Streamlit to compare data between them. Check out the GitHub repository for more!

Face Recognition

I used the Face Recognition library to create a Streamlit dashboard that allows multiple face recognition when in front of the camera. In case the face is not recognized, the dashboard shows it as unknown.

Pharmacy Sales Analysis

I surveyed the client to determine which data points to extract from their system, then created a Google Sheets template for the dashboard. The client uploads their Excel file to Google Sheets weekly, which automatically updates the dashboard.

Netflix Movie Duration Analysis

I applied my skills in Python to solve a real-world data science problem. The goal was to discover if Netflix’s movies are getting shorter over time and which guest stars appear in the most popular episode of "The Office", using everything from lists and loops to pandas and matplotlib.

Analyzing International Debt Statistics

In this project, I am going to analyze international debt data collected by The World Bank. The dataset contains information about the amount of debt (in USD) owed by developing countries across several categories.